Index (JMSL Numerical Library)

Overview

Package

Class

Tree

Index

Help

JMSL^TM Numerical Library 4.0

PREV NEXT

FRAMES NO FRAMES

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A

ADJUSTED_R_SQUARED_CRITERION - Static variable in class com.imsl.stat.SelectionRegression: Indicates (adjusted ) criterion regression.
AFTER_SUCCESSFUL_STEP - Static variable in class com.imsl.math.OdeRungeKutta: Used by method examineStep to indicate examining after a successful step
AFTER_UNSUCCESSFUL_STEP - Static variable in class com.imsl.math.OdeRungeKutta: Used by method examineStep to indicate examining after an unsuccessful step
ALPHA_FACTOR_ANALYSIS - Static variable in class com.imsl.stat.FactorAnalysis: Indicates alpha factor analysis.
ANNUAL - Static variable in class com.imsl.finance.Bond: Coupon payments are made annually.
ANOVA - class com.imsl.stat.ANOVA.: Analysis of Variance table and related statistics.
ANOVA(double[][]) - Constructor for class com.imsl.stat.ANOVA: Analyzes a one-way classification model.
ANOVA(double, double, double, double, double) - Constructor for class com.imsl.stat.ANOVA: Construct an analysis of variance table and related statistics.
ANOVAFactorial - class com.imsl.stat.ANOVAFactorial.: Analyzes a balanced factorial design with fixed effects.
ANOVAFactorial(int, int[], double[]) - Constructor for class com.imsl.stat.ANOVAFactorial: Constructor for ANOVAFactorial.
ARMA - class com.imsl.stat.ARMA.: Computes least-square estimates of parameters for an ARMA model.
ARMA(int, int, double[]) - Constructor for class com.imsl.stat.ARMA: Constructor for ARMA.
ARMA.IllConditionedException - exception com.imsl.stat.ARMA.IllConditionedException.: The problem is ill-conditioned.
ARMA.IllConditionedException(String) - Constructor for class com.imsl.stat.ARMA.IllConditionedException: Constructs an IllConditionedException with the specified detail message.
ARMA.IllConditionedException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.IllConditionedException: Constructs an IllConditionedException with the specified detail message.
ARMA.IncreaseErrRelException - exception com.imsl.stat.ARMA.IncreaseErrRelException.: The bound for the relative error is too small.
ARMA.IncreaseErrRelException(String) - Constructor for class com.imsl.stat.ARMA.IncreaseErrRelException: Constructs an IncreaseErrRelException with the specified detail message.
ARMA.IncreaseErrRelException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.IncreaseErrRelException: Constructs an IncreaseErrRelException with the specified detail message.
ARMA.MatrixSingularException - exception com.imsl.stat.ARMA.MatrixSingularException.: The input matrix is singular.
ARMA.MatrixSingularException(String) - Constructor for class com.imsl.stat.ARMA.MatrixSingularException: Constructs an MatrixSingularException with the specified detail message.
ARMA.MatrixSingularException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.MatrixSingularException: Constructs an MatrixSingularException with the specified detail message.
ARMA.NewInitialGuessException - exception com.imsl.stat.ARMA.NewInitialGuessException.: The iteration has not made good progress.
ARMA.NewInitialGuessException(String) - Constructor for class com.imsl.stat.ARMA.NewInitialGuessException: Constructs an NewInitialGuessException with the specified detail message.
ARMA.NewInitialGuessException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.NewInitialGuessException: Constructs an NewInitialGuessException with the specified detail message.
ARMA.TooManyCallsException - exception com.imsl.stat.ARMA.TooManyCallsException.: The number of calls to the function has exceeded the maximum number of iterations.
ARMA.TooManyCallsException(String) - Constructor for class com.imsl.stat.ARMA.TooManyCallsException: Constructs an TooManyCallsException with the specified detail message.
ARMA.TooManyCallsException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.TooManyCallsException: Constructs an TooManyCallsException with the specified detail message.
ARMA.TooManyFcnEvalException - exception com.imsl.stat.ARMA.TooManyFcnEvalException.: Maximum number of function evaluations exceeded.
ARMA.TooManyFcnEvalException(String) - Constructor for class com.imsl.stat.ARMA.TooManyFcnEvalException: Constructs an TooManyFcnEvalException with the specified detail message.
ARMA.TooManyFcnEvalException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.TooManyFcnEvalException: Constructs an TooManyFcnEvalException with the specified detail message.
ARMA.TooManyITNException - exception com.imsl.stat.ARMA.TooManyITNException.: Maximum number of iterations exceeded.
ARMA.TooManyITNException(String) - Constructor for class com.imsl.stat.ARMA.TooManyITNException: Constructs an TooManyITNException with the specified detail message.
ARMA.TooManyITNException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.TooManyITNException
ARMA.TooManyJacobianEvalException - exception com.imsl.stat.ARMA.TooManyJacobianEvalException.: Maximum number of Jacobian evaluations exceeded.
ARMA.TooManyJacobianEvalException(String) - Constructor for class com.imsl.stat.ARMA.TooManyJacobianEvalException: Constructs an TooManyJacobianEvalException with the specified detail message.
ARMA.TooManyJacobianEvalException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.TooManyJacobianEvalException: Constructs an TooManyJacobianEvalException with the specified detail message.
AT_BEGINNING_OF_PERIOD - Static variable in class com.imsl.finance.Finance: Flag used to indicate that payment is made at the beginning of each period.
AT_END_OF_PERIOD - Static variable in class com.imsl.finance.Finance: Flag used to indicate that payment is made at the end of each period.
AUTOSCALE_DATA - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is to be done by scanning the data nodes.
AUTOSCALE_DENSITY - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is to adjust the "Density" attribute.
AUTOSCALE_NUMBER - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is to adjust the "Number" attribute.
AUTOSCALE_OFF - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is turned off.
AUTOSCALE_WINDOW - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is to be done by using the "Window" attribute.
AXIS_TITLE_AT_END - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "AxisTitlePosition" indicating that the axis title should be placed at the end of the axis.
AXIS_TITLE_PARALLEL - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "AxisTitlePosition" indicating that the axis title should be placed parallel to the axis.
AXIS_X - Static variable in class com.imsl.chart.AbstractChartNode: Flag to indicate x-axis.
AXIS_X_TOP - Static variable in class com.imsl.chart.ChartNode: Flag to indicate x-axis placed on top of the chart.
AXIS_Y - Static variable in class com.imsl.chart.AbstractChartNode: Flag to indicate y-axis.
AXIS_Y_RIGHT - Static variable in class com.imsl.chart.ChartNode: Flag to indicate y-axis placed to the right of the chart.
AXIS_Z - Static variable in class com.imsl.chart.AbstractChartNode: Flag to indicate z-axis.
AbstractChartNode - class com.imsl.chart.AbstractChartNode.: The base class of all of the nodes in both the 2D and 3D chart trees.
AbstractChartNode(AbstractChartNode) - Constructor for class com.imsl.chart.AbstractChartNode
AbstractFlatFile - class com.imsl.io.AbstractFlatFile.: Reads a text or binary file as a ResultSet.
AbstractFlatFile() - Constructor for class com.imsl.io.AbstractFlatFile: Initializes an AbstractFlatFile.
AbstractFlatFile.FlatFileSQLException - exception com.imsl.io.AbstractFlatFile.FlatFileSQLException.: A SQLException thrown by the AbstractFlatFile class.
Activation - interface com.imsl.datamining.neural.Activation.: Interface implemented by perceptron activation functions.
AmbientLight - class com.imsl.chart3d.AmbientLight.: An ambient light.
AmbientLight(Chart3D) - Constructor for class com.imsl.chart3d.AmbientLight: Creates an ambient light.
AutoCorrelation - class com.imsl.stat.AutoCorrelation.: Computes the sample autocorrelation function of a stationary time series.
AutoCorrelation(double[], int) - Constructor for class com.imsl.stat.AutoCorrelation: Constructor to compute the sample autocorrelation function of a stationary time series.
AutoCorrelation.NonPosVariancesException - exception com.imsl.stat.AutoCorrelation.NonPosVariancesException.: The problem is ill-conditioned.
AutoCorrelation.NonPosVariancesException(String) - Constructor for class com.imsl.stat.AutoCorrelation.NonPosVariancesException: Constructs an NonPosVariancesException with the specified detail message.
AutoCorrelation.NonPosVariancesException(String, Object[]) - Constructor for class com.imsl.stat.AutoCorrelation.NonPosVariancesException: Constructs an NonPosVariancesException with the specified detail message.
Axis - class com.imsl.chart.Axis.: The Axis node provides the mapping for all of its children from the user coordinate space to the device (screen) space.
Axis(Chart) - Constructor for class com.imsl.chart.Axis: Contructs an Axis node.
Axis1D - class com.imsl.chart.Axis1D.: An x-axis or a y-axis.
Axis3D - class com.imsl.chart3d.Axis3D.: An x-axis, y-axis or a z-axis.
AxisBox - class com.imsl.chart3d.AxisBox.: Box behind the axis.
AxisLabel - class com.imsl.chart.AxisLabel.: The labels on an axis.
AxisLabel - class com.imsl.chart3d.AxisLabel.: The labels on an axis.
AxisLine - class com.imsl.chart.AxisLine.: The axis line.
AxisLine - class com.imsl.chart3d.AxisLine.: The axis line.
AxisR - class com.imsl.chart.AxisR.: The R-axis in a polar plot.
AxisRLabel - class com.imsl.chart.AxisRLabel.: The labels on an axis.
AxisRLine - class com.imsl.chart.AxisRLine.: The radius axis line in a polar plot.
AxisRMajorTick - class com.imsl.chart.AxisRMajorTick.: The major tick marks for the radius axis in a polar plot.
AxisTheta - class com.imsl.chart.AxisTheta.: The angular axis in a polar plot.
AxisTitle - class com.imsl.chart.AxisTitle.: The title on an axis.
AxisTitle - class com.imsl.chart3d.AxisTitle.: Axis title.
AxisUnit - class com.imsl.chart.AxisUnit.: The unit title on an axis.
AxisXY - class com.imsl.chart.AxisXY.: The axes for an x-y chart.
AxisXY(Chart) - Constructor for class com.imsl.chart.AxisXY: Create an AxisXY.
AxisXYZ - class com.imsl.chart3d.AxisXYZ.: The axes for an x-y-z chart.
AxisXYZ(Chart3D) - Constructor for class com.imsl.chart3d.AxisXYZ: Create an AxisXYZ.
abs(Complex) - Static method in class com.imsl.math.Complex: Returns the absolute value (modulus) of a Complex, |z|.
abs(int) - Static method in class com.imsl.math.JMath: Returns the absolute value of an int.
abs(long) - Static method in class com.imsl.math.JMath: Returns the absolute value of a long.
abs(float) - Static method in class com.imsl.math.JMath: Returns the absolute value of a float.
abs(double) - Static method in class com.imsl.math.JMath: Returns the absolute value of a double.
absolute(int) - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the given row number in this ResultSet object.
accrint(GregorianCalendar, GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the interest which has accrued on a security that pays interest periodically.
accrintm(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the interest which has accrued on a security that pays interest at maturity.
acos(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse cosine (arc cosine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.
acos(double) - Static method in class com.imsl.math.JMath: Returns the inverse (arc) cosine of a double.
acosh(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse hyperbolic cosine (arc cosh) of a Complex, with a branch cut at values less than one along the real axis.
acosh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the inverse hyperbolic cosine of its argument.
add(Complex, Complex) - Static method in class com.imsl.math.Complex: Returns the sum of two Complex objects, x+y.
add(Complex, double) - Static method in class com.imsl.math.Complex: Returns the sum of a Complex and a double, x+y.
add(double, Complex) - Static method in class com.imsl.math.Complex: Returns the sum of a double and a Complex, x+y.
add(Complex[][], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Add two rectangular Complex arrays, a + b.
add(double[][], double[][]) - Static method in class com.imsl.math.Matrix: Add two rectangular arrays, a + b.
add(Physical, Physical) - Static method in class com.imsl.math.Physical: Add two compatible Physical objects.
addLegendItem(int, ChartNode) - Method in class com.imsl.chart.Chart: Adds a legend to this ChartNode
addMouseListener(MouseListener) - Method in class com.imsl.chart.Chart: Adds a MouseListener to the component associated with this chart.
addMouseMotionListener(MouseMotionListener) - Method in class com.imsl.chart.Chart: Adds a MouseMotionListener to the component associated with this chart.
addNode(Node) - Method in class com.imsl.datamining.neural.Layer: Associates a Perceptron with this Layer.
addPickListener(PickListener) - Method in class com.imsl.chart.ChartNode: Adds a PickListener to this node.
addPostRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart: Adds a Paint object to draw to the canvas after the the 3D image is rendered.
addPreRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart: Adds a Paint object to draw to the canvas before the the 3D image is rendered.
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AmbientLight
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Axis3D
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisBox
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisLabel
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisLine
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisTitle
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisXYZ
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Background
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Chart3D
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ChartLights
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ChartNode3D: Called to add this object to the scene graph.
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ColormapLegend
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Data
addToSceneGraph(Group) - Method in class com.imsl.chart3d.DirectionalLight
addToSceneGraph(Group) - Method in class com.imsl.chart3d.MajorTick
addToSceneGraph(Group) - Method in class com.imsl.chart3d.PointLight
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Surface
afterLast() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the end of this ResultSet object, just after the last row.
allConverged() - Method in class com.imsl.math.ZeroFunction: Returns true if the iterations for all of the roots have converged.
amordegrc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the depreciation for each accounting period.
amorlinc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the depreciation for each accounting period.
argument(Complex) - Static method in class com.imsl.math.Complex: Returns the argument (phase) of a Complex, in radians, with a branch cut along the negative real axis.
ascending(double[], int[]) - Static method in class com.imsl.stat.Sort: Sort an array into ascending order.
ascending(int[], int[]) - Static method in class com.imsl.stat.Sort: Sort an array into ascending order.
ascending(double[]) - Static method in class com.imsl.stat.Sort: Sort an array into ascending order.
ascending(int[]) - Static method in class com.imsl.stat.Sort: Function to sort an integer array into ascending order.
ascending(double[][], int) - Static method in class com.imsl.stat.Sort: Sort a matrix into ascending order by specified keys.
ascending(double[][], int[]) - Static method in class com.imsl.stat.Sort: Sort a matrix into ascending order by specified keys.
ascending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort: Sort an array into ascending order by specified keys.
ascending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort: Sort a matrix into ascending order by specified keys.
asin(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse sine (arc sine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.
asin(double) - Static method in class com.imsl.math.JMath: Returns the inverse (arc) sine of a double.
asinh(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse hyperbolic sine (arc sinh) of a Complex, with branch cuts outside the interval [-i,i].
asinh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the inverse hyperbolic sine of its argument.
atan(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse tangent (arc tangent) of a Complex, with branch cuts outside the interval [-i,i] along the imaginary axis.
atan(double) - Static method in class com.imsl.math.JMath: Returns the inverse (arc) tangent of a double.
atan2(double, double) - Static method in class com.imsl.math.JMath: Returns the angle corresponding to a Cartesian point.
atanh(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse hyperbolic tangent (arc tanh) of a Complex, with branch cuts outside the interval [-1,1] on the real axis.
atanh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the inverse hyperbolic tangent of its argument.

B

BACKWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression: Indicates backward regression.
BARTLETTS_FORMULA - Static variable in class com.imsl.stat.AutoCorrelation: Indicates standard error computation using Bartlett's formula.
BARTLETTS_FORMULA - Static variable in class com.imsl.stat.CrossCorrelation: Indicates standard error computation using Bartlett's formula.
BARTLETTS_FORMULA_NOCC - Static variable in class com.imsl.stat.CrossCorrelation: Indicates standard error computation using Bartlett's formula with the assumption of no cross-correlation.
BAR_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.ChartNode: Flag to indicate a horizontal bar chart.
BAR_TYPE_VERTICAL - Static variable in class com.imsl.chart.ChartNode: Flag to indicate a vertical bar chart.
BEFORE_STEP - Static variable in class com.imsl.math.OdeRungeKutta: Used by method examineStep to indicate examining before the next step
BEGIN_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.
BEGIN_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for beginning a column label row is to be returned.
BEGIN_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatted string for beginning an entry is to be returned.
BEGIN_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for beginning a matrix is to be returned.
BEGIN_ROW - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for beginning a row is to be returned.
BEGIN_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for beginning a row label is to be returned.
BINARY_VARIABLE - Static variable in class com.imsl.io.MPSReader: Variable must be either 0 or 1.
BLUE - Static variable in interface com.imsl.chart.Colormap: Linear blue colormap.
BLUE_GREEN_RED_YELLOW - Static variable in interface com.imsl.chart.Colormap: Blue/green/red/yellow colormap.
BLUE_RED - Static variable in interface com.imsl.chart.Colormap: Blue/red colormap.
BLUE_WHITE - Static variable in interface com.imsl.chart.Colormap: Blue/white colormap.
BOUNDED_SCALING - Static variable in class com.imsl.datamining.neural.ScaleFilter: Flag to indicate bounded scaling.
BOUNDED_Z_SCORE_SCALING_MEAN_STDEV - Static variable in class com.imsl.datamining.neural.ScaleFilter: Flag to indicate bounded z-score scaling using the mean and standard deviation.
BOUNDED_Z_SCORE_SCALING_MEDIAN_MAD - Static variable in class com.imsl.datamining.neural.ScaleFilter: Flag to indicate bounded z-score scaling using the median and mean absolute difference.
BOXPLOT_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.BoxPlot: Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.
BOXPLOT_TYPE_VERTICAL - Static variable in class com.imsl.chart.BoxPlot: Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.
BSpline - class com.imsl.math.BSpline.: BSpline represents and evaluates univariate B-splines.
BSpline() - Constructor for class com.imsl.math.BSpline
BW_LINEAR - Static variable in interface com.imsl.chart.Colormap: Black and white (grayscale) colormap.
Background - class com.imsl.chart.Background.: The background of a chart.
Background - class com.imsl.chart3d.Background.: Background of the chart.
Bar - class com.imsl.chart.Bar.: A bar chart.
Bar(AxisXY) - Constructor for class com.imsl.chart.Bar: Constructs a bar chart.
Bar(AxisXY, double[]) - Constructor for class com.imsl.chart.Bar: Constructs a simple bar chart using supplied y data.
Bar(AxisXY, double[], double[]) - Constructor for class com.imsl.chart.Bar: Constructs a simple bar chart using supplied x and y data.
Bar(AxisXY, double[][]) - Constructor for class com.imsl.chart.Bar: Constructs a grouped bar chart using supplied x and y data.
Bar(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.Bar: Constructs a grouped bar chart using supplied x and y data.
Bar(AxisXY, double[][][]) - Constructor for class com.imsl.chart.Bar: Constructs a stacked, grouped bar chart using supplied y data.
Bar(AxisXY, double[], double[][][]) - Constructor for class com.imsl.chart.Bar: Constructs a stacked, grouped bar chart using supplied x and y data.
BarItem - class com.imsl.chart.BarItem.: A single bar in a bar chart.
BarSet - class com.imsl.chart.BarSet.: A set of bars in a bar chart.
Basis30e360 - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 30 days per month and 360 days per year.
BasisActual360 - Static variable in class com.imsl.finance.DayCountBasis: Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 360 days per year.
BasisActual365 - Static variable in class com.imsl.finance.DayCountBasis: Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 365 days per year.
BasisActualActual - Static variable in class com.imsl.finance.DayCountBasis: Computations are based on the actual calendar.
BasisNASD - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 30 days per month and 360 days per year.
BasisPart - interface com.imsl.finance.BasisPart.: Component of DayCountBasis.
BasisPart30E360 - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 30 days per month and 360 days per year.
BasisPart365 - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 365 days per year.
BasisPartActual - Static variable in class com.imsl.finance.DayCountBasis: Computations are based on the actual calendar.
BasisPartNASD - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 30 days per month and 360 days per year.
Bessel - class com.imsl.math.Bessel.: Collection of Bessel functions.
BinaryClassification - class com.imsl.datamining.neural.BinaryClassification.: Classifies patterns into two classes.
BinaryClassification(Network) - Constructor for class com.imsl.datamining.neural.BinaryClassification: Creates a binary classifier.
Bond - class com.imsl.finance.Bond.: Collection of bond functions.
Bond() - Constructor for class com.imsl.finance.Bond
BoundedLeastSquares - class com.imsl.math.BoundedLeastSquares.: Solves a nonlinear least-squares problem subject to bounds on the variables using a modified Levenberg-Marquardt algorithm.
BoundedLeastSquares(BoundedLeastSquares.Function, int, int, int, double[], double[]) - Constructor for class com.imsl.math.BoundedLeastSquares: Constructor for BoundedLeastSquares.
BoundedLeastSquares.FalseConvergenceException - exception com.imsl.math.BoundedLeastSquares.FalseConvergenceException.: False convergence - The iterates appear to be converging to a noncritical point.
BoundedLeastSquares.FalseConvergenceException(String) - Constructor for class com.imsl.math.BoundedLeastSquares.FalseConvergenceException: Constructs an FalseConvergenceException with the specified detail message.
BoundedLeastSquares.FalseConvergenceException(String, Object[]) - Constructor for class com.imsl.math.BoundedLeastSquares.FalseConvergenceException: Constructs an FalseConvergenceException with the specified detail message.
BoundedLeastSquares.Function - interface com.imsl.math.BoundedLeastSquares.Function.: Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.
BoundedLeastSquares.Jacobian - interface com.imsl.math.BoundedLeastSquares.Jacobian.: Public interface for the user-supplied function to compute the Jacobian.
BoxPlot - class com.imsl.chart.BoxPlot.: Draws a multiple-group Box plot.
BoxPlot(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.BoxPlot: Constructs a box plot chart node with specified x values.
BoxPlot(AxisXY, double[], BoxPlot.Statistics[]) - Constructor for class com.imsl.chart.BoxPlot: Constructs a box plot chart node with specified x values.
BoxPlot(AxisXY, double[][]) - Constructor for class com.imsl.chart.BoxPlot: Constructs a box plot chart.
BoxPlot.Statistics - class com.imsl.chart.BoxPlot.Statistics.: Computes the statistics for one set of observations in a Boxplot.
BoxPlot.Statistics(double[]) - Constructor for class com.imsl.chart.BoxPlot.Statistics: Creates a new instance of BoxPlot.Statistics.
BsInterpolate - class com.imsl.math.BsInterpolate.: Extension of the BSpline class to interpolate data points.
BsInterpolate(double[], double[]) - Constructor for class com.imsl.math.BsInterpolate: Constructs a B-spline that interpolates the given data points.
BsInterpolate(double[], double[], int) - Constructor for class com.imsl.math.BsInterpolate: Constructs a B-spline that interpolates the given data points and order, using a default "not-a-knot" spline knot sequence.
BsInterpolate(double[], double[], int, double[]) - Constructor for class com.imsl.math.BsInterpolate: Constructs a B-spline that interpolates the given data points, using the specified order and knots.
BsLeastSquares - class com.imsl.math.BsLeastSquares.: Extension of the BSpline class to compute a least squares spline approximation to data points.
BsLeastSquares(double[], double[], int) - Constructor for class com.imsl.math.BsLeastSquares: Constructs a least squares B-spline approximation to the given data points.
BsLeastSquares(double[], double[], int, int) - Constructor for class com.imsl.math.BsLeastSquares: Constructs a least squares B-spline approximation to the given data points.
BsLeastSquares(double[], double[], int, int, double[], double[]) - Constructor for class com.imsl.math.BsLeastSquares: Constructs a least squares B-spline approximation to the given data points.
BufferedPaint - class com.imsl.chart3d.BufferedPaint.: A Paint object cached into an image.
BufferedPaint(Canvas3DChart.Paint, int, int, int, int, Component) - Constructor for class com.imsl.chart3d.BufferedPaint: The paint method in Canvas3DChart.Paint is written into an image of size width by height.
backward(Complex[]) - Method in class com.imsl.math.ComplexFFT: Compute the complex periodic sequence from its Fourier coefficients.
backward(double[]) - Method in class com.imsl.math.FFT: Compute the real periodic sequence from its Fourier coefficients.
basis(int, double) - Method in interface com.imsl.stat.RegressionBasis: Public interface for the nonlinear least-squares function.
beforeFirst() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the front of this ResultSet object, just before the first row.
beginGet() - Method in class com.imsl.io.AbstractFlatFile: This method should be called at the start of every getType method.
beta(double, double) - Static method in class com.imsl.math.Sfun: Returns the value of the Beta function.
beta(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the beta cumulative probability distribution function.
betaIncomplete(double, double, double) - Static method in class com.imsl.math.Sfun: Returns the incomplete Beta function ratio.
betaMean(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the mean of the beta cumulative probability distribution function
betaProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the beta probability density function.
betaVariance(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the variance of the beta cumulative probability distribution function
binomial(int, int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the binomial cumulative probability distribution function.
binomialProb(int, int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the binomial probability density function.
bivariateNormal(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the bivariate normal cumulative probability distribution function.
breakPoint - Variable in class com.imsl.math.Spline: The breakpoint array of length n, where n is the number of piecewise polynomials.
byteValue() - Method in class com.imsl.math.Complex: Returns the value of the real part as a byte.

C

COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatted string for a given column label is to be returned.
CONTINUOUS_VARIABLE - Static variable in class com.imsl.io.MPSReader: Variable is a real number.
CORRECTED_SSCP_MATRIX - Static variable in class com.imsl.stat.Covariances: Indicates corrected sums of squares and crossproducts matrix.
CORRELATION_MATRIX - Static variable in class com.imsl.stat.Covariances: Indicates correlation matrix.
CORRELATION_MATRIX - Static variable in class com.imsl.stat.FactorAnalysis: Indicates correlation matrix.
CURRENT - Static variable in class com.imsl.math.Physical
Candlestick - class com.imsl.chart.Candlestick.: Candlestick plot of stock data.
Candlestick(AxisXY, Date, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick: Constructs a candlestick chart node beginning with specified start date.
Candlestick(AxisXY, double[], double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick: Constructs a candlestick chart node at specified axis points.
CandlestickItem - class com.imsl.chart.CandlestickItem.: A candlestick for the up days or the down days.
Canvas3DChart - class com.imsl.chart3d.Canvas3DChart.: A canvas for rendering a 3D chart.
Canvas3DChart() - Constructor for class com.imsl.chart3d.Canvas3DChart: Creates a Canvas3DChart with a new Chart3D object.
Canvas3DChart(Chart3D) - Constructor for class com.imsl.chart3d.Canvas3DChart: Creates a Canvas3DChart with a given Chart3D object.
Canvas3DChart.Paint - interface com.imsl.chart3d.Canvas3DChart.Paint.: Interface for 2D drawing on the canvas before or after the the 3D image is drawn.
CategoricalGenLinModel - class com.imsl.stat.CategoricalGenLinModel.: Analyzes categorical data using logistic, probit, Poisson, and other linear models.
CategoricalGenLinModel(double[][], int) - Constructor for class com.imsl.stat.CategoricalGenLinModel: Constructs a new CategoricalGenLinModel.
CategoricalGenLinModel.ClassificationVariableException - exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableException.: The ClassificationVariable vector has not been initialized.
CategoricalGenLinModel.ClassificationVariableException() - Constructor for class com.imsl.stat.CategoricalGenLinModel.ClassificationVariableException: Constructs a ClassificationVariableException.
CategoricalGenLinModel.ClassificationVariableLimitException - exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableLimitException.: The Classification Variable limit set by the user through setUpperBound has been exceeded.
CategoricalGenLinModel.ClassificationVariableLimitException(int) - Constructor for class com.imsl.stat.CategoricalGenLinModel.ClassificationVariableLimitException: Constructs a ClassificationVariableLimitException.
CategoricalGenLinModel.ClassificationVariableValueException - exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableValueException.: The number of distinct values for each Classification Variable must be greater than 1.
CategoricalGenLinModel.ClassificationVariableValueException(int, int) - Constructor for class com.imsl.stat.CategoricalGenLinModel.ClassificationVariableValueException: Constructs a ClassificationVariableValueException.
CategoricalGenLinModel.DeleteObservationsException - exception com.imsl.stat.CategoricalGenLinModel.DeleteObservationsException.: The number of observations to be deleted (set by setObservationMax) has grown too large.
CategoricalGenLinModel.DeleteObservationsException(int) - Constructor for class com.imsl.stat.CategoricalGenLinModel.DeleteObservationsException: Constructs a DeleteObservationsException.
Cdf - class com.imsl.stat.Cdf.: Cumulative probability distribution functions, probability density functions, and their inverses.
CdfFunction - interface com.imsl.stat.CdfFunction.: Public interface for the user-supplied cumulative distribution function to be used by InverseCdf and ChiSquaredTest.
Chart - class com.imsl.chart.Chart.: The root node of the chart tree.
Chart() - Constructor for class com.imsl.chart.Chart: This is the root of our tree, it has no parent.
Chart(Component) - Constructor for class com.imsl.chart.Chart: This is the root of our tree, it has no parent.
Chart(Image) - Constructor for class com.imsl.chart.Chart: This is the root of our tree, it has no parent.
Chart3D - class com.imsl.chart3d.Chart3D.: Root node of a 3d chart tree.
Chart3D() - Constructor for class com.imsl.chart3d.Chart3D: Creates a new instance of Chart3D
ChartFunction - interface com.imsl.chart.ChartFunction.: An interface that allows a function to be plotted.
ChartLights - class com.imsl.chart3d.ChartLights.: Default set of lights.
ChartNode - class com.imsl.chart.ChartNode.: The base class of all of the nodes in the 2D chart tree.
ChartNode(ChartNode) - Constructor for class com.imsl.chart.ChartNode: Construct a ChartNode object.
ChartNode3D - class com.imsl.chart3d.ChartNode3D.: The base class of all of the nodes in the 3D chart tree.
ChartNode3D(ChartNode3D) - Constructor for class com.imsl.chart3d.ChartNode3D: Construct a ChartNode3D object.
ChartServlet - class com.imsl.chart.ChartServlet.: The base class for chart servlets.
ChartServlet() - Constructor for class com.imsl.chart.ChartServlet
ChartSpline - class com.imsl.chart.ChartSpline.: Wrap a spline into a ChartFunction to be plotted.
ChartSpline(Spline) - Constructor for class com.imsl.chart.ChartSpline: Creates a ChartSpline from a Spline.
ChartSpline(Spline, int) - Constructor for class com.imsl.chart.ChartSpline: Creates a ChartSpline from the derivative of a Spline.
ChartTitle - class com.imsl.chart.ChartTitle.: The main title of a chart.
ChartXML - class com.imsl.chart.xml.ChartXML.: Create a Chart from an XML file.
ChartXML(String) - Constructor for class com.imsl.chart.xml.ChartXML: Creates a ChartXML from an XML file.
ChartXML(String, boolean) - Constructor for class com.imsl.chart.xml.ChartXML: Creates a ChartXML from an XML file.
ChartXML(InputSource, boolean) - Constructor for class com.imsl.chart.xml.ChartXML: Creates a ChartXML from an XML source.
ChartXML(Document) - Constructor for class com.imsl.chart.xml.ChartXML: Creates a ChartXML from a DOM tree.
ChiSquaredTest - class com.imsl.stat.ChiSquaredTest.: Chi-squared goodness-of-fit test.
ChiSquaredTest(CdfFunction, double[], int) - Constructor for class com.imsl.stat.ChiSquaredTest: Constructor for the Chi-squared goodness-of-fit test.
ChiSquaredTest(CdfFunction, int, int) - Constructor for class com.imsl.stat.ChiSquaredTest: Constructor for the Chi-squared goodness-of-fit test
ChiSquaredTest(int) - Method in class com.imsl.stat.NormalityTest: Performs the chi-squared goodness-of-fit test.
ChiSquaredTest.DidNotConvergeException - exception com.imsl.stat.ChiSquaredTest.DidNotConvergeException.: The iteration did not converge
ChiSquaredTest.DidNotConvergeException(String) - Constructor for class com.imsl.stat.ChiSquaredTest.DidNotConvergeException
ChiSquaredTest.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.stat.ChiSquaredTest.DidNotConvergeException
ChiSquaredTest.NoObservationsException - exception com.imsl.stat.ChiSquaredTest.NoObservationsException.: There are no observations.
ChiSquaredTest.NoObservationsException(String, Object[]) - Constructor for class com.imsl.stat.ChiSquaredTest.NoObservationsException
ChiSquaredTest.NotCDFException - exception com.imsl.stat.ChiSquaredTest.NotCDFException.: The function is not a Cumulative Distribution Function (CDF).
ChiSquaredTest.NotCDFException(String, Object[]) - Constructor for class com.imsl.stat.ChiSquaredTest.NotCDFException
Cholesky - class com.imsl.math.Cholesky.: Cholesky factorization of a matrix of type double.
Cholesky(double[][]) - Constructor for class com.imsl.math.Cholesky: Create the Cholesky factorization of a symmetric positive definite matrix of type double.
Cholesky.NotSPDException - exception com.imsl.math.Cholesky.NotSPDException.: The matrix is not symmetric, positive definite.
Cholesky.NotSPDException() - Constructor for class com.imsl.math.Cholesky.NotSPDException
ClusterHierarchical - class com.imsl.stat.ClusterHierarchical.: Performs a hierarchical cluster analysis from a distance matrix.
ClusterHierarchical(double[][], int, int) - Constructor for class com.imsl.stat.ClusterHierarchical: Constructor for ClusterHierarchical.
ClusterKMeans - class com.imsl.stat.ClusterKMeans.: Perform a K-means (centroid) cluster analysis.
ClusterKMeans(double[][], double[][]) - Constructor for class com.imsl.stat.ClusterKMeans: Constructor for ClusterKMeans.
ClusterKMeans.ClusterNoPointsException - exception com.imsl.stat.ClusterKMeans.ClusterNoPointsException.: There is a cluster with no points
ClusterKMeans.ClusterNoPointsException(String) - Constructor for class com.imsl.stat.ClusterKMeans.ClusterNoPointsException
ClusterKMeans.ClusterNoPointsException(String, Object[]) - Constructor for class com.imsl.stat.ClusterKMeans.ClusterNoPointsException
ClusterKMeans.NoConvergenceException - exception com.imsl.stat.ClusterKMeans.NoConvergenceException.: Convergence did not occur within the maximum number of iterations.
ClusterKMeans.NoConvergenceException(String) - Constructor for class com.imsl.stat.ClusterKMeans.NoConvergenceException
ClusterKMeans.NoConvergenceException(String, Object[]) - Constructor for class com.imsl.stat.ClusterKMeans.NoConvergenceException
ClusterKMeans.NonnegativeFreqException - exception com.imsl.stat.ClusterKMeans.NonnegativeFreqException.: Frequencies must be nonnegative.
ClusterKMeans.NonnegativeFreqException(String) - Constructor for class com.imsl.stat.ClusterKMeans.NonnegativeFreqException
ClusterKMeans.NonnegativeFreqException(String, Object[]) - Constructor for class com.imsl.stat.ClusterKMeans.NonnegativeFreqException
ClusterKMeans.NonnegativeWeightException - exception com.imsl.stat.ClusterKMeans.NonnegativeWeightException.: Weights must be nonnegative.
ClusterKMeans.NonnegativeWeightException(String) - Constructor for class com.imsl.stat.ClusterKMeans.NonnegativeWeightException
ClusterKMeans.NonnegativeWeightException(String, Object[]) - Constructor for class com.imsl.stat.ClusterKMeans.NonnegativeWeightException
ColorFunction - interface com.imsl.chart3d.ColorFunction.: Interface to define value dependent colors.
Colormap - interface com.imsl.chart.Colormap.: Colormaps are mappings from the unit interval to Colors.
ColormapLegend - class com.imsl.chart3d.ColormapLegend.: Adds a legend for a Colormap gradient to the background of the canvas.
ColormapLegend(Chart3D, Colormap, double[]) - Constructor for class com.imsl.chart3d.ColormapLegend: Creates a legend for a Colormap and adds it to the canvas.
ColormapLegend(Chart3D, Colormap, double, double) - Constructor for class com.imsl.chart3d.ColormapLegend
Complex - class com.imsl.math.Complex.: Set of mathematical functions for complex numbers.
Complex(Complex) - Constructor for class com.imsl.math.Complex: Constructs a Complex equal to the argument.
Complex(double, double) - Constructor for class com.imsl.math.Complex: Constructs a Complex with real and imaginary parts given by the input arguments.
Complex(double) - Constructor for class com.imsl.math.Complex: Constructs a Complex with a zero imaginary part.
Complex() - Constructor for class com.imsl.math.Complex: Constructs a Complex equal to zero.
ComplexFFT - class com.imsl.math.ComplexFFT.: Complex FFT.
ComplexFFT(int) - Constructor for class com.imsl.math.ComplexFFT: Constructs a complex FFT object.
ComplexLU - class com.imsl.math.ComplexLU.: LU factorization of a matrix of type Complex.
ComplexLU(Complex[][]) - Constructor for class com.imsl.math.ComplexLU: Creates the LU factorization of a square matrix of type Complex.
ComplexMatrix - class com.imsl.math.ComplexMatrix.: Complex matrix manipulation functions.
ContingencyTable - class com.imsl.stat.ContingencyTable.: Performs a chi-squared analysis of a two-way contingency table.
ContingencyTable(double[][]) - Constructor for class com.imsl.stat.ContingencyTable: Constructs and performs a chi-squared analysis of a two-way contingency table.
Contour - class com.imsl.chart.Contour.: A Contour chart shows level curves of a two-dimensional function.
Contour(AxisXY, double[], double[], double[][], double[]) - Constructor for class com.imsl.chart.Contour: Create a Contour chart from rectangularly gridded data.
Contour(AxisXY, double[], double[], double[][]) - Constructor for class com.imsl.chart.Contour: Create a Contour chart from rectangularly gridded data with computed contour levels.
Contour(AxisXY, double[], double[], double[]) - Constructor for class com.imsl.chart.Contour: Create a Contour chart from scattered data with computed contour levels.
Contour(AxisXY, double[], double[], double[], double[], int) - Constructor for class com.imsl.chart.Contour: Create a Contour chart from scattered data.
Contour.Legend - class com.imsl.chart.Contour.Legend.: A legend for a contour chart.
ContourLevel - class com.imsl.chart.ContourLevel.: ContourLevel draws a level curve line and the fill area between the level curve and the next smaller level curve.
Covariances - class com.imsl.stat.Covariances.: Computes the sample variance-covariance or correlation matrix.
Covariances(double[][]) - Constructor for class com.imsl.stat.Covariances: Constructor for Covariances.
Covariances.DiffObsDeletedException - exception com.imsl.stat.Covariances.DiffObsDeletedException.: Different observations are being deleted from return matrix than were originally entered.
Covariances.DiffObsDeletedException(String) - Constructor for class com.imsl.stat.Covariances.DiffObsDeletedException
Covariances.DiffObsDeletedException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.DiffObsDeletedException
Covariances.MoreObsDelThanEnteredException - exception com.imsl.stat.Covariances.MoreObsDelThanEnteredException.: More observations are being deleted from the output covariance matrix than were originally entered (the corresponding row, column of the incidence matrix is less than zero).
Covariances.MoreObsDelThanEnteredException(String) - Constructor for class com.imsl.stat.Covariances.MoreObsDelThanEnteredException
Covariances.MoreObsDelThanEnteredException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.MoreObsDelThanEnteredException
Covariances.NonnegativeFreqException - exception com.imsl.stat.Covariances.NonnegativeFreqException.: Frequencies must be nonnegative.
Covariances.NonnegativeFreqException(String) - Constructor for class com.imsl.stat.Covariances.NonnegativeFreqException
Covariances.NonnegativeFreqException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.NonnegativeFreqException
Covariances.NonnegativeWeightException - exception com.imsl.stat.Covariances.NonnegativeWeightException.: Weights must be nonnegative.
Covariances.NonnegativeWeightException(String) - Constructor for class com.imsl.stat.Covariances.NonnegativeWeightException
Covariances.NonnegativeWeightException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.NonnegativeWeightException
Covariances.TooManyObsDeletedException - exception com.imsl.stat.Covariances.TooManyObsDeletedException.: More observations have been deleted than were originally entered (the sum of frequencies has become negative).
Covariances.TooManyObsDeletedException(String) - Constructor for class com.imsl.stat.Covariances.TooManyObsDeletedException
Covariances.TooManyObsDeletedException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.TooManyObsDeletedException
CrossCorrelation - class com.imsl.stat.CrossCorrelation.: Computes the sample cross-correlation function of two stationary time series.
CrossCorrelation(double[], double[], int) - Constructor for class com.imsl.stat.CrossCorrelation: Constructor to compute the sample cross-correlation function of two stationary time series.
CrossCorrelation.NonPosVariancesException - exception com.imsl.stat.CrossCorrelation.NonPosVariancesException.: The problem is ill-conditioned.
CrossCorrelation.NonPosVariancesException(String) - Constructor for class com.imsl.stat.CrossCorrelation.NonPosVariancesException
CrossCorrelation.NonPosVariancesException(String, Object[]) - Constructor for class com.imsl.stat.CrossCorrelation.NonPosVariancesException
CsAkima - class com.imsl.math.CsAkima.: Extension of the Spline class to handle the Akima cubic spline.
CsAkima(double[], double[]) - Constructor for class com.imsl.math.CsAkima: Constructs the Akima cubic spline interpolant to the given data points.
CsInterpolate - class com.imsl.math.CsInterpolate.: Extension of the Spline class to interpolate data points.
CsInterpolate(double[], double[]) - Constructor for class com.imsl.math.CsInterpolate: Constructs a cubic spline that interpolates the given data points.
CsInterpolate(double[], double[], int, double, int, double) - Constructor for class com.imsl.math.CsInterpolate: Constructs a cubic spline that interpolates the given data points with specified derivative endpoint conditions.
CsPeriodic - class com.imsl.math.CsPeriodic.: Extension of the Spline class to interpolate data points with periodic boundary conditions.
CsPeriodic(double[], double[]) - Constructor for class com.imsl.math.CsPeriodic: Constructs a cubic spline that interpolates the given data points with periodic boundary conditions.
CsShape - class com.imsl.math.CsShape.: Extension of the Spline class to interpolate data points consistent with the concavity of the data.
CsShape(double[], double[]) - Constructor for class com.imsl.math.CsShape: Construct a cubic spline interpolant which is consistent with the concavity of the data.
CsShape.TooManyIterationsException - exception com.imsl.math.CsShape.TooManyIterationsException.: Too many iterations.
CsShape.TooManyIterationsException() - Constructor for class com.imsl.math.CsShape.TooManyIterationsException
CsShape.TooManyIterationsException(String, Object[]) - Constructor for class com.imsl.math.CsShape.TooManyIterationsException
CsShape.TooManyIterationsException(Object[]) - Constructor for class com.imsl.math.CsShape.TooManyIterationsException
CsSmooth - class com.imsl.math.CsSmooth.: Extension of the Spline class to construct a smooth cubic spline from noisy data points.
CsSmooth(double[], double[]) - Constructor for class com.imsl.math.CsSmooth: Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.
CsSmooth(double[], double[], double[]) - Constructor for class com.imsl.math.CsSmooth: Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.
CsSmoothC2 - class com.imsl.math.CsSmoothC2.: Extension of the Spline class used to construct a spline for noisy data points using an alternate method.
CsSmoothC2(double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2: Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967).
CsSmoothC2(double[], double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2: Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967) with weights supplied by the user.
cancelRowUpdates() - Method in class com.imsl.io.AbstractFlatFile: Cancels the updates made to the current row in this ResultSet object.
cdf(double) - Method in interface com.imsl.stat.CdfFunction: Public interface for the user-supplied cumulative distribution function to be used by InverseCdf.
ceil(double) - Static method in class com.imsl.math.JMath: Returns the value of a double rounded toward positive infinity to an integral value.
chart - Variable in class com.imsl.chart.JPanelChart: The embedded chart.
check(int) - Static method in class com.imsl.Messages
check(int) - Method in class com.imsl.chart.Draw
checkCompatibility(Physical, Physical) - Static method in class com.imsl.math.Physical: Checks the compatibility of two Physical objects.
checkMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Check that all of the rows in the Complex matrix have the same length.
checkMatrix(double[][]) - Static method in class com.imsl.math.Matrix: Check that all of the rows in the matrix have the same length.
checkSquareMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Check that the Complex matrix is square.
checkSquareMatrix(double[][]) - Static method in class com.imsl.math.Matrix: Check that the matrix is square.
checkerboard(int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a checkerboard pattern.
chi(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the chi-squared cumulative probability distribution function.
chiMean(double) - Static method in class com.imsl.stat.Cdf: Evaluates the mean of the chi-squared cumulative probability distribution function
chiProb(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the chi-squared probability density function
chiVariance(double) - Static method in class com.imsl.stat.Cdf: Evaluates the variance of the chi-squared cumulative probability distribution function
circle(int, int, int) - Method in class com.imsl.chart.DrawMap: Sets a circle as the target.
cleanup() - Method in class com.imsl.chart3d.Chart3D: Cleanup memory use and references used by the chart.
clearWarnings() - Method in class com.imsl.io.AbstractFlatFile: Clears all warnings reported on this ResultSet object.
clone(Map) - Method in class com.imsl.chart.AbstractChartNode: Returns a deep-copy clone of this node.
clone(Object, Map) - Method in class com.imsl.chart.AbstractChartNode: Returns a deep copy of an Object.
clone(Map, Map) - Method in class com.imsl.chart.AbstractChartNode: Returns a deep copy of a Hashtable.
clone(List, Map) - Method in class com.imsl.chart.AbstractChartNode: Returns a deep copy of a vector of ChartNode's.
clone() - Method in class com.imsl.chart.Chart: Returns a clone of the graphics tree.
clone(Map) - Method in class com.imsl.chart.Chart: Returns a clone of this node.
clone() - Method in class com.imsl.chart3d.Chart3D: Returns a clone of the graphics tree.
clone(Map) - Method in class com.imsl.chart3d.Chart3D: Returns a clone of this node.
clone() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Clones a copy of the trainer.
clone() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Clones a copy of the trainer.
clone() - Method in class com.imsl.math.DenseLP: Creates and returns a copy of this object.
clone() - Method in class com.imsl.math.LinearProgramming: Creates and returns a copy of this object.
clone() - Method in class com.imsl.stat.FaureSequence: Returns a copy of this object.
clone() - Method in class com.imsl.stat.MersenneTwister: Returns a clone of this object.
clone() - Method in class com.imsl.stat.MersenneTwister64: Returns a clone of this object.
close() - Method in class com.imsl.io.AbstractFlatFile: Releases this ResultSet object's database and JDBC resources immediately instead of waiting for this to happen when it is automatically closed.
coef - Variable in class com.imsl.math.BSpline: The B-spline coefficient array.
coef - Variable in class com.imsl.math.Spline: Coefficients of the piecewise polynomials.
color(double) - Method in interface com.imsl.chart.Colormap: Maps the parameterization interval [0,1] into Colors.
color(double, double, double) - Method in interface com.imsl.chart3d.ColorFunction
com.imsl - package com.imsl
com.imsl.chart - package com.imsl.chart
com.imsl.chart.xml - package com.imsl.chart.xml
com.imsl.chart3d - package com.imsl.chart3d
com.imsl.datamining.neural - package com.imsl.datamining.neural
com.imsl.finance - package com.imsl.finance
com.imsl.io - package com.imsl.io
com.imsl.math - package com.imsl.math
com.imsl.stat - package com.imsl.stat
compareTo(Object) - Method in class com.imsl.math.Complex: Compares this Complex to another Object.
compareTo(Complex) - Method in class com.imsl.math.Complex: Compares two Complex objects.
compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Function: Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.
compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Jacobian: Public interface for the user-supplied function to compute the Jacobian.
compute() - Method in class com.imsl.stat.ANOVAFactorial: Analyzes a balanced factorial design with fixed effects.
compute() - Method in class com.imsl.stat.ARMA: Computes least-square estimates of parameters for an ARMA model.
compute() - Method in class com.imsl.stat.ClusterKMeans: Computes the cluster means.
compute(int) - Method in class com.imsl.stat.Covariances: Computes the matrix.
compute(double[], int[]) - Method in class com.imsl.stat.Difference: Computes a Difference series.
compute() - Method in class com.imsl.stat.GARCH: Computes estimates of the parameters of a GARCH(p,q) model.
compute() - Static method in class com.imsl.stat.KaplanMeierECDF: Computes the empirical CDF
compute() - Method in class com.imsl.stat.MultipleComparisons: Performs Student-Newman-Keuls multiple comparisons test.
compute(double[][], double[]) - Method in class com.imsl.stat.SelectionRegression: Computes the best multiple linear regression models.
compute(double[][], double[], double[]) - Method in class com.imsl.stat.SelectionRegression: Computes the best weighted multiple linear regression models.
compute(double[][], double[], double[], double[]) - Method in class com.imsl.stat.SelectionRegression: Computes the best weighted multiple linear regression models using frequencies for each observation.
compute(double[][], int) - Method in class com.imsl.stat.SelectionRegression: Computes the best multiple linear regression models using a user-supplied covariance matrix.
compute() - Method in class com.imsl.stat.SignTest: Performs a sign test.
compute() - Method in class com.imsl.stat.StepwiseRegression: Builds the multiple linear regression models using forward selection, backward selection, or stepwise selection.
compute() - Method in class com.imsl.stat.WilcoxonRankSum: Performs a Wilcoxon rank sum test.
computeLags(int[], int[], double[]) - Method in class com.imsl.datamining.neural.TimeSeriesClassFilter: Computes lags of an array sorted first by class designations and then descending chronological order.
computeLags(int, double[][]) - Method in class com.imsl.datamining.neural.TimeSeriesFilter: Lags time series data to a format used for input to a neural network.
computeMin(MinUncon.Function) - Method in class com.imsl.math.MinUncon: Return the minimum of a smooth function of a single variable of type double using function values only or using function values and derivatives.
computeMin(MinUnconMultiVar.Function) - Method in class com.imsl.math.MinUnconMultiVar: Return the minimum point of a function of n variables of type double using a finite-difference gradient or using a user-supplied gradient.
computeRoots(double[]) - Method in class com.imsl.math.ZeroPolynomial: Computes the roots of the polynomial with real coefficients.
computeRoots(Complex[]) - Method in class com.imsl.math.ZeroPolynomial: Computes the roots of the polynomial with Complex coefficients.
computeStatistics(double[][], int[]) - Method in class com.imsl.datamining.neural.BinaryClassification: Computes the classification error statistics for the supplied network patterns and their associated classifications.
computeStatistics(double[][], int[]) - Method in class com.imsl.datamining.neural.MultiClassification: Computes classification statistics for the supplied network patterns and their associated classifications.
computeStatistics(double[][], double[][]) - Method in class com.imsl.datamining.neural.Network: Computes error statistics.
computeZeros(ZeroFunction.Function, double[]) - Method in class com.imsl.math.ZeroFunction: Returns the zeros of a univariate function.
condition(Complex[][]) - Method in class com.imsl.math.ComplexLU: Return an estimate of the reciprocal of the L1 condition number.
condition(double[][]) - Method in class com.imsl.math.LU: Return an estimate of the reciprocal of the L1 condition number of a matrix.
confidenceMean(double) - Method in class com.imsl.stat.Summary: Returns the confidence interval for the mean (assuming normality).
confidenceVariance(double) - Method in class com.imsl.stat.Summary: Returns the confidence interval for the variance (assuming normality).
conjugate(Complex) - Static method in class com.imsl.math.Complex: Returns the complex conjugate of a Complex object.
constant(String) - Static method in class com.imsl.math.Physical: Returns the value of a constant, given its name.
constant(String, String) - Static method in class com.imsl.math.Physical: Returns the value of a constant, given its name, in the specified units.
convert(Physical, String) - Static method in class com.imsl.math.Physical: Converts a value to a different set of units.
convexity(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the convexity for a security.
copy() - Method in class com.imsl.chart.Chart: Copy the chart to the clipboard.
copyAndSortData(double[], double[]) - Method in class com.imsl.math.Spline: Copy and sort xData into breakPoint and yData into the first column of coef.
copyAndSortData(double[], double[], double[]) - Method in class com.imsl.math.Spline: Copy and sort xData into breakPoint and yData into the first column of coef.
copysign(double, double) - Static method in class com.imsl.math.IEEE: Returns a value with the magnitude of x and with the sign bit of y.
cos(Complex) - Static method in class com.imsl.math.Complex: Returns the cosine of a Complex.
cos(double) - Static method in class com.imsl.math.JMath: Returns the cosine of a double.
cosh(Complex) - Static method in class com.imsl.math.Complex: Returns the hyperbolic cosh of a Complex.
cosh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the hyperbolic cosine of its argument.
cot(double) - Static method in class com.imsl.math.Sfun: Returns the cotangent of a double.
countTokens() - Method in class com.imsl.io.Tokenizer: Returns the number of times that the nextToken method can be called without generating an exception.
coupdaybs(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the number of days starting with the beginning of the coupon period and ending with the settlement date.
coupdays(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the number of days in the coupon period containing the settlement date.
coupdaysnc(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the number of days starting with the settlement date and ending with the next coupon date.
coupncd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the first coupon date which follows the settlement date.
coupnum(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the number of coupons payable between the settlement date and the maturity date.
couppcd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the coupon date which immediately precedes the settlement date.
createCustomMarker() - Method in interface com.imsl.chart3d.Data.CustomMarkerFactory: Returns a custom marker.
createHiddenLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Creates a HiddenLayer.
createHiddenLayer() - Method in class com.imsl.datamining.neural.Network: Creates the next HiddenLayer in the Network.
createInput() - Method in class com.imsl.datamining.neural.InputLayer: Creates an InputNode in the InputLayer of the neural network.
createInputs(int) - Method in class com.imsl.datamining.neural.InputLayer: Creates a number of InputNodes in this Layer of the neural network.
createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer: Creates a Perceptron in this Layer with a specified activation function and bias.
createPerceptron() - Method in class com.imsl.datamining.neural.HiddenLayer: Creates a Perceptron in this Layer of the neural network.
createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer: Creates a Perceptron in this Layer with a specified Activation and bias.
createPerceptron() - Method in class com.imsl.datamining.neural.OutputLayer: Creates a Perceptron in this Layer of the neural network.
createPerceptrons(int) - Method in class com.imsl.datamining.neural.HiddenLayer: Creates a number of Perceptrons in this Layer of the neural network.
createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer: Creates a number of Perceptrons in this Layer with the specified bias.
createPerceptrons(int) - Method in class com.imsl.datamining.neural.OutputLayer: Creates a number of Perceptrons in this Layer of the neural network.
createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer: Creates a number of Perceptrons in this Layer with specified activation and bias.
crosshatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a horizonal and vertical crosshatch pattern.
cumipmt(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance: Returns the cumulative interest paid between two periods.
cumprinc(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance: Returns the cumulative principal paid between two periods.
currentType - Variable in class com.imsl.chart.Draw

D

DASH_PATTERN_DASH - Static variable in class com.imsl.chart.ChartNode: Flag to draw a dashed line.
DASH_PATTERN_DASH_DOT - Static variable in class com.imsl.chart.ChartNode: Flag to draw a dash-dot pattern line.
DASH_PATTERN_DOT - Static variable in class com.imsl.chart.ChartNode: Flag to draw a dotted line.
DASH_PATTERN_SOLID - Static variable in class com.imsl.chart.ChartNode: Flag to draw solid line.
DATA_TYPE_ERROR_X - Static variable in class com.imsl.chart.ErrorBar: Value for attribute "DataType" indicating that this is a horizontal error bar.
DATA_TYPE_ERROR_Y - Static variable in class com.imsl.chart.ErrorBar: Value for attribute "DataType" indicating that this is a vertical error bar.
DATA_TYPE_FILL - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that the area between the lines connecting the data points and the horizontal reference line (y = attribute "Reference") should be filled.
DATA_TYPE_LINE - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that the data points should be connected with line segments.
DATA_TYPE_LINE - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "DataType" indicating that the data points should be connected with line segments.
DATA_TYPE_MARKER - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that a marker should be drawn at each data point.
DATA_TYPE_MARKER - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "DataType" indicating that a marker should be drawn at each data point.
DATA_TYPE_PICTURE - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that an image (attribute "Image") should be drawn at each data point.
DATA_TYPE_PICTURE - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "DataType" indicating that an image (attribute "Image") should be drawn at each data point.
DATA_TYPE_TUBE - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that an a tube connecting the data points should be drawn.
DATA_TYPE_TUBE - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "DataType" indicating that a tube connecting the data points should be drawn.
DAY - Static variable in class com.imsl.chart.HighLowClose: Milliseconds per day
DENDROGRAM_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.ChartNode: Flag to indicate a horizontal dendrogram.
DENDROGRAM_TYPE_VERTICAL - Static variable in class com.imsl.chart.ChartNode: Flag to indicate a vertical dendrogram.
Data - class com.imsl.chart.Data.: Draws a data node.
Data(ChartNode) - Constructor for class com.imsl.chart.Data: Creates a data node.
Data(ChartNode, double[]) - Constructor for class com.imsl.chart.Data: Creates a data node with y values.
Data(ChartNode, ChartFunction, double, double) - Constructor for class com.imsl.chart.Data: Creates a data node with y values.
Data(ChartNode, double[], double[]) - Constructor for class com.imsl.chart.Data: Creates a data node with x and y values.
Data - class com.imsl.chart3d.Data.: Draws a 3D data node.
Data(AxisXYZ) - Constructor for class com.imsl.chart3d.Data: Creates a data node.
Data(AxisXYZ, double[], double[], double[]) - Constructor for class com.imsl.chart3d.Data: Creates a data node with x, y and z values.
Data.CustomMarkerFactory - interface com.imsl.chart3d.Data.CustomMarkerFactory.: Factory to create customized markers.
DayCountBasis - class com.imsl.finance.DayCountBasis.: The Day Count Basis.
DayCountBasis(BasisPart, BasisPart) - Constructor for class com.imsl.finance.DayCountBasis: Creates a new DayCountBasis.
Dendrogram - class com.imsl.chart.Dendrogram.: A Dendrogram chart for cluster analysis.
Dendrogram(AxisXY, ClusterHierarchical) - Constructor for class com.imsl.chart.Dendrogram: Constructs a vertical dendrogram chart using supplied ClusterHierarchical object.
Dendrogram(AxisXY, double[], int[], int[]) - Constructor for class com.imsl.chart.Dendrogram: Constructs a vertical dendrogram chart using supplied data.
Dendrogram(AxisXY, ClusterHierarchical, int) - Constructor for class com.imsl.chart.Dendrogram: Constructs a dendrogram chart using supplied ClusterHierarchical object.
Dendrogram(AxisXY, double[], int[], int[], int) - Constructor for class com.imsl.chart.Dendrogram: Constructs a dendrogram chart using supplied data.
DenseLP - class com.imsl.math.DenseLP.: Solves a linear programming problem using an active set strategy.
DenseLP(MPSReader) - Constructor for class com.imsl.math.DenseLP: Constructor using an MPSReader object.
DenseLP(double[][], double[], double[]) - Constructor for class com.imsl.math.DenseLP: Constructor variables of type double.
DenseLP.BoundsInconsistentException - exception com.imsl.math.DenseLP.BoundsInconsistentException.: The bounds given are inconsistent.
DenseLP.BoundsInconsistentException(String) - Constructor for class com.imsl.math.DenseLP.BoundsInconsistentException
DenseLP.BoundsInconsistentException(String, Object[]) - Constructor for class com.imsl.math.DenseLP.BoundsInconsistentException
DenseLP.NoAcceptablePivotException - exception com.imsl.math.DenseLP.NoAcceptablePivotException.: No acceptable pivot could be found.
DenseLP.NoAcceptablePivotException(String) - Constructor for class com.imsl.math.DenseLP.NoAcceptablePivotException
DenseLP.NoAcceptablePivotException(String, Object[]) - Constructor for class com.imsl.math.DenseLP.NoAcceptablePivotException
DenseLP.ProblemUnboundedException - exception com.imsl.math.DenseLP.ProblemUnboundedException.: The problem is unbounded.
DenseLP.ProblemUnboundedException(String) - Constructor for class com.imsl.math.DenseLP.ProblemUnboundedException
DenseLP.ProblemUnboundedException(String, Object[]) - Constructor for class com.imsl.math.DenseLP.ProblemUnboundedException
Difference - class com.imsl.stat.Difference.: Differences a seasonal or nonseasonal time series.
Difference() - Constructor for class com.imsl.stat.Difference: Constructor for Difference.
DirectionalLight - class com.imsl.chart3d.DirectionalLight.: A directional light.
DirectionalLight(Chart3D) - Constructor for class com.imsl.chart3d.DirectionalLight: Creates a directional light pointing in the negative z direction.
DirectionalLight(Chart3D, double, double, double) - Constructor for class com.imsl.chart3d.DirectionalLight: Creates a directional light pointing with a specified direction.
DiscriminantAnalysis - class com.imsl.stat.DiscriminantAnalysis.: Performs a linear or a quadratic discriminant function analysis among several known groups and the use of either reclassification, split sample, or the leaving-out-one methods in order to evaluate the rule.
DiscriminantAnalysis(int, int) - Constructor for class com.imsl.stat.DiscriminantAnalysis: Constructor for DiscriminantAnalysis.
DiscriminantAnalysis.CovarianceSingularException - exception com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException.: The variance-Covariance matrix is singular.
DiscriminantAnalysis.CovarianceSingularException(String) - Constructor for class com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException
DiscriminantAnalysis.CovarianceSingularException(String, Object[]) - Constructor for class com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException
DiscriminantAnalysis.EmptyGroupException - exception com.imsl.stat.DiscriminantAnalysis.EmptyGroupException.: There are no observations in a group.
DiscriminantAnalysis.EmptyGroupException(String) - Constructor for class com.imsl.stat.DiscriminantAnalysis.EmptyGroupException
DiscriminantAnalysis.EmptyGroupException(String, Object[]) - Constructor for class com.imsl.stat.DiscriminantAnalysis.EmptyGroupException
DiscriminantAnalysis.SumOfWeightsNegException - exception com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException.: The sum of the weights have become negative.
DiscriminantAnalysis.SumOfWeightsNegException(String) - Constructor for class com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException
DiscriminantAnalysis.SumOfWeightsNegException(String, Object[]) - Constructor for class com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException
Dissimilarities - class com.imsl.stat.Dissimilarities.: Computes a matrix of dissimilarities (or similarities) between the columns (or rows) of a matrix.
Dissimilarities(double[][], int, int, int) - Constructor for class com.imsl.stat.Dissimilarities: Constructor for Dissimilarities.
Dissimilarities(double[][], int, int, int, int[]) - Constructor for class com.imsl.stat.Dissimilarities: Constructor for Dissimilarities.
Dissimilarities.NoPositiveVarianceException - exception com.imsl.stat.Dissimilarities.NoPositiveVarianceException.: No variable has positive variance.
Dissimilarities.NoPositiveVarianceException() - Constructor for class com.imsl.stat.Dissimilarities.NoPositiveVarianceException: Constructs a NoPositiveVarianceException.
Dissimilarities.ScaleFactorZeroException - exception com.imsl.stat.Dissimilarities.ScaleFactorZeroException.: The computations cannot continue because a scale factor is zero.
Dissimilarities.ScaleFactorZeroException(int) - Constructor for class com.imsl.stat.Dissimilarities.ScaleFactorZeroException: Constructs a ScaleFactorZeroException.
Dissimilarities.ZeroNormException - exception com.imsl.stat.Dissimilarities.ZeroNormException.: The computations cannot continue because the Euclidean norm of the column is equal to zero.
Dissimilarities.ZeroNormException(int) - Constructor for class com.imsl.stat.Dissimilarities.ZeroNormException: Constructs a ZeroNormException.
Draw - class com.imsl.chart.Draw.: Chart tree renderer.
Draw(Graphics, Dimension) - Constructor for class com.imsl.chart.Draw: Contructs a Draw object.
DrawMap - class com.imsl.chart.DrawMap.: Creates an HTML client-side imagemap from a chart tree.
DrawMap(Graphics, Dimension) - Constructor for class com.imsl.chart.DrawMap: Contructs a DrawMap object.
DrawPick - class com.imsl.chart.DrawPick.: The DrawPick class.
DrawPick(MouseEvent, Graphics, Dimension) - Constructor for class com.imsl.chart.DrawPick: Contructs a DrawPick object.
Dummy - class com.imsl.Dummy.
Dummy() - Constructor for class com.imsl.Dummy
dataRange(double[]) - Method in class com.imsl.chart.Bar: Overrides Data.dataRange.
dataRange(double[]) - Method in class com.imsl.chart.BarItem: Overides Data.dataRange.
dataRange(double[]) - Method in class com.imsl.chart.BarSet
dataRange(double[]) - Method in class com.imsl.chart.BoxPlot: Overrides Data.dataRange.
dataRange(double[]) - Method in class com.imsl.chart.Contour: Update the data range.
dataRange(double[]) - Method in class com.imsl.chart.Data: Update the data range.
dataRange(double[]) - Method in class com.imsl.chart.Dendrogram: Overrides Data.dataRange.
dataRange(double[]) - Method in class com.imsl.chart.ErrorBar: Overrides Data.dataRange.
dataRange(double[]) - Method in class com.imsl.chart.Heatmap: Update the data range.
dataRange(double[]) - Method in class com.imsl.chart.HighLowClose: Overrides Data.dataRange.
dataRange(double[]) - Method in class com.imsl.chart3d.Data: Update the data range.
dataRange(double[]) - Method in class com.imsl.chart3d.Surface: Update the data range.
daysBetween(GregorianCalendar, GregorianCalendar) - Method in interface com.imsl.finance.BasisPart: Returns the number of days from date1 to date2.
daysInPeriod(GregorianCalendar, int) - Method in interface com.imsl.finance.BasisPart: Returns the number of days in a coupon period.
db(double, double, int, int, int) - Static method in class com.imsl.finance.Finance: Returns the depreciation of an asset using the fixed-declining balance method.
ddb(double, double, int, int, double) - Static method in class com.imsl.finance.Finance: Returns the depreciation of an asset using the double-declining balance method.
decode(double) - Method in class com.imsl.datamining.neural.ScaleFilter: Unscales a value.
decode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter: Unscales an array of values.
decode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter: Unscales a single column of a two dimensional array of values.
decode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Decodes a binary encoded array into its nominal category.
decode(int[][]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Decodes a matrix representing the binary encoded columns of the nominal variable.
decode(double) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Decodes an encoded ordinal variable.
decode(double[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Decodes an array of encoded ordinal values.
defineConstant(String, Physical) - Static method in class com.imsl.math.Physical: Defines a new constant.
definePrefix(String, double) - Static method in class com.imsl.math.Physical: Defines a new prefix.
defineUnit(String, Physical) - Static method in class com.imsl.math.Physical: Defines a new unit.
deleteRow() - Method in class com.imsl.io.AbstractFlatFile: Deletes the current row from this ResultSet object and from the underlying database.
derivative(double, double) - Method in interface com.imsl.datamining.neural.Activation: Returns the value of the derivative of the activation function.
derivative(double) - Method in class com.imsl.math.BSpline: Returns the value of the first derivative of the B-spline at a point.
derivative(double, int) - Method in class com.imsl.math.BSpline: Returns the value of the derivative of the B-spline at a point.
derivative(double[], int) - Method in class com.imsl.math.BSpline: Returns the value of the derivative of the B-spline at each point of an array.
derivative(double) - Method in class com.imsl.math.Spline: Returns the value of the first derivative of the spline at a point.
derivative(double, int) - Method in class com.imsl.math.Spline: Returns the value of the derivative of the spline at a point.
derivative(double[], int) - Method in class com.imsl.math.Spline: Returns the value of the derivative of the spline at each point of an array.
derivative(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Derivative: Computes the weight, frequency, and partial derivatives of the residual given the parameter vector theta for a single observation.
descending(double[], int[]) - Static method in class com.imsl.stat.Sort: Sort an array into descending order.
descending(double[]) - Static method in class com.imsl.stat.Sort: Sort an array into descending order.
descending(double[][], int) - Static method in class com.imsl.stat.Sort: Function to sort a matrix into descending order by specified keys.
descending(double[][], int[]) - Static method in class com.imsl.stat.Sort: Function to sort a matrix into descending order by specified keys.
descending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort: Function to sort an array into descending order by specified keys.
descending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort: Function to sort a matrix into descending order by specified keys.
determinant() - Method in class com.imsl.math.ComplexLU: Return the determinant of the matrix used to construct this instance.
determinant() - Method in class com.imsl.math.LU: Return the determinant of the matrix used to construct this instance.
diagonal(int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a diagonal pattern.
diamond(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a diamond pattern (a checkerboard rotated 45 degrees).
diamondHatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a crosshatch on a 45 degree angle.
dim - Variable in class com.imsl.math.Physical
disc(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the implied interest rate of a discount bond.
discreteUniform(int, int) - Static method in class com.imsl.stat.Cdf: Evaluates the discrete uniform cumulative probability distribution function.
discreteUniformProb(int, int) - Static method in class com.imsl.stat.Cdf: Evaluates the discrete uniform probability density function.
divide(Complex, Complex) - Static method in class com.imsl.math.Complex: Returns the result of a Complex object divided by a Complex object, x/y.
divide(Complex, double) - Static method in class com.imsl.math.Complex: Returns the result of a Complex object divided by a double, x/y.
divide(double, Complex) - Static method in class com.imsl.math.Complex: Returns the result of a double divided by a Complex object, x/y.
divide(Physical, Physical) - Static method in class com.imsl.math.Physical: Divide two Physical objects.
divide(Physical, double) - Static method in class com.imsl.math.Physical: Divide a Physical object by a double.
divide(double, Physical) - Static method in class com.imsl.math.Physical: Divide a double by a Physical object.
doGet(HttpServletRequest, HttpServletResponse) - Method in class com.imsl.chart.ChartServlet: Returns the chart as a PNG image.
doGetBytes(int) - Method in class com.imsl.io.AbstractFlatFile: Implements the actual getBytes().
doGetBytes(int) - Method in class com.imsl.io.FlatFile: Gets the value of the designated column in the current row as a byte array.
doNext() - Method in class com.imsl.io.AbstractFlatFile: Implements the operations on the file required by the method next().
doNext() - Method in class com.imsl.io.FlatFile: Moves the cursor down one row from its current position.
dollarde(double, int) - Static method in class com.imsl.finance.Finance: Converts a fractional price to a decimal price.
dollarfr(double, int) - Static method in class com.imsl.finance.Finance: Converts a decimal price to a fractional price.
dot(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a pattern that is an array of circles.
doubleValue() - Method in class com.imsl.math.Complex: Returns the value of the real part as a double.
doubleValue() - Method in class com.imsl.math.Physical: Returns the value of this dimensionless object.
downdate(double[]) - Method in class com.imsl.math.Cholesky: Downdates the factorization by subtracting a rank-1 matrix.
downdateX(double[]) - Method in class com.imsl.stat.NormTwoSample: Removes the observations in x from the first sample.
downdateY(double[]) - Method in class com.imsl.stat.NormTwoSample: Removes the observations in y from the second sample.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw: Draws the outline of a circular or elliptical arc covering the specified rectangle.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap: Draws the outline of a circular or elliptical arc covering the specified rectangle.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick: Draw an arc.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.Draw: Draw an error bar.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.DrawMap: Draw an error bar.
drawErrorBar(int, int, int, int) - Method in class com.imsl.chart.DrawPick: Draw ErrorBar
drawImage(Image, int, int) - Method in class com.imsl.chart.Draw: Draw an image.
drawImage(Image, int, int) - Method in class com.imsl.chart.DrawMap: Draw Image
drawImage(Image, int, int) - Method in class com.imsl.chart.DrawPick: Draw Image
drawLine(int, int, int, int) - Method in class com.imsl.chart.Draw: Draw a line from (x0,y0) to (x1,y1).
drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawMap: Draw a line from (x0,y0) to (x1,y1).
drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawPick: Draw a line from (x0,y0) to (x1,y1).
drawMarker(int, int) - Method in class com.imsl.chart.Draw: Draw a marker.
drawMarker(int, int) - Method in class com.imsl.chart.DrawMap: Draw a marker.
drawMarker(int, int) - Method in class com.imsl.chart.DrawPick: Draw a marker.
drawRotatedText(Text, int, int, float) - Method in class com.imsl.chart.Draw: Draws a text object, at the specified angle, with its lower left point being at (x,y).
drawText(Text, int, int) - Method in class com.imsl.chart.Draw: Draws a text object.
drawText(Text, int, int, boolean) - Method in class com.imsl.chart.Draw: Draws a text object.
drawText(Graphics, Text) - Method in class com.imsl.chart.Draw: Draws the text.
drawText(Text, int, int, boolean) - Method in class com.imsl.chart.DrawMap
drawText(Text, int, int) - Method in class com.imsl.chart.DrawPick
duration(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the Macauley's duration of a security where the security has periodic interest payments.

E

E - Static variable in class com.imsl.math.JMath
END_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.
END_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a column label row is to be returned.
END_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatted string for ending an entry is to be returned.
END_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a matrix is to be returned.
END_ROW - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a row is to be returned.
END_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a row label is to be returned.
ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatted string for a given entry is to be returned.
EPSILON_LARGE - Static variable in class com.imsl.math.Sfun: The largest relative spacing for doubles.
EPSILON_LARGE - Static variable in class com.imsl.math.Spline: The largest relative spacing for double.
EPSILON_SMALL - Static variable in class com.imsl.math.QuadraticProgramming: The smallest relative spacing for doubles.
EPSILON_SMALL - Static variable in class com.imsl.math.Sfun: The smallest relative spacing for doubles.
EPSILON_SMALL - Static variable in class com.imsl.math.ZeroPolynomial: The smallest relative spacing for doubles.
ERROR_BAR - Static variable in class com.imsl.chart.Draw
Eigen - class com.imsl.math.Eigen.: Collection of Eigen System functions.
Eigen(double[][]) - Constructor for class com.imsl.math.Eigen: Constructs the eigenvalues and the eigenvectors of a real square matrix.
Eigen(double[][], boolean) - Constructor for class com.imsl.math.Eigen: Constructs the eigenvalues and (optionally) the eigenvectors of a real square matrix.
Eigen.DidNotConvergeException - exception com.imsl.math.Eigen.DidNotConvergeException.: The iteration did not converge
Eigen.DidNotConvergeException(String) - Constructor for class com.imsl.math.Eigen.DidNotConvergeException
Eigen.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.math.Eigen.DidNotConvergeException
EmpiricalQuantiles - class com.imsl.stat.EmpiricalQuantiles.: Computes empirical quantiles.
EmpiricalQuantiles(double[], double[]) - Constructor for class com.imsl.stat.EmpiricalQuantiles: Constructor for EmpiricalQuantiles.
EmpiricalQuantiles.ScaleFactorZeroException - exception com.imsl.stat.EmpiricalQuantiles.ScaleFactorZeroException.: The computations cannot continue because a scale factor is zero.
EmpiricalQuantiles.ScaleFactorZeroException(int) - Constructor for class com.imsl.stat.EmpiricalQuantiles.ScaleFactorZeroException: Constructs a ScaleFactorZeroException.
EpochTrainer - class com.imsl.datamining.neural.EpochTrainer.: Two-stage training using randomly selected training patterns in stage I.
EpochTrainer(Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer: Creates a single stage EpochTrainer.
EpochTrainer(Trainer, Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer: Creates an two-stage EpochTrainer.
EpsilonAlgorithm - class com.imsl.math.EpsilonAlgorithm.: The class is used to determine the limit of a sequence of approximations, by means of the Epsilon algorithm of P.
EpsilonAlgorithm() - Constructor for class com.imsl.math.EpsilonAlgorithm: Initializes an EpsilonAlgorithm with a maximum table size of 50.
EpsilonAlgorithm(int) - Constructor for class com.imsl.math.EpsilonAlgorithm: Initializes an EpsilonAlgorithm.
ErrorBar - class com.imsl.chart.ErrorBar.: Data points with error bars.
ErrorBar(AxisXY, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.ErrorBar: Creates a set of error bars centered at (x[k],y[k]) and with extents low[k],high[k].
effect(double, int) - Static method in class com.imsl.finance.Finance: Returns the effective annual interest rate.
encode(double) - Method in class com.imsl.datamining.neural.ScaleFilter: Scales a value.
encode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter: Scales an array of values.
encode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter: Scales a single column of a two dimensional array of values.
encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Encodes class data prior to its use in neural network training.
encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Apply forward encoding to a value.
encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Encodes an array of ordinal categories into an array of transformed percentages.
encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Encodes an ordinal category.
endErrorBar() - Method in class com.imsl.chart.Draw: Stop drawing an error bar.
endErrorBar() - Method in class com.imsl.chart.DrawMap
endErrorBar() - Method in class com.imsl.chart.DrawPick: End ErrorBar
endFill() - Method in class com.imsl.chart.Draw: Stop drawing a filled region.
endFill() - Method in class com.imsl.chart.DrawMap
endFill() - Method in class com.imsl.chart.DrawPick: End fill
endImage() - Method in class com.imsl.chart.Draw: Stop drawing an image.
endImage() - Method in class com.imsl.chart.DrawMap
endImage() - Method in class com.imsl.chart.DrawPick: End Image
endLine() - Method in class com.imsl.chart.Draw: Finish drawing lines.
endLine() - Method in class com.imsl.chart.DrawMap
endLine() - Method in class com.imsl.chart.DrawPick: Finish drawing lines.
endMarker() - Method in class com.imsl.chart.Draw: Finish drawing markers.
endMarker() - Method in class com.imsl.chart.DrawMap
endMarker() - Method in class com.imsl.chart.DrawPick: Finish drawing markers.
endText() - Method in class com.imsl.chart.Draw: Stop drawing text.
endText() - Method in class com.imsl.chart.DrawMap
endText() - Method in class com.imsl.chart.DrawPick: End Text
equals(Complex) - Method in class com.imsl.math.Complex: Compares with another Complex.
equals(Object) - Method in class com.imsl.math.Complex: Compares this object against the specified object.
erf(double) - Static method in class com.imsl.math.Sfun: Returns the error function of a double.
erfInverse(double) - Static method in class com.imsl.math.Sfun: Returns the inverse of the error function.
erfc(double) - Static method in class com.imsl.math.Sfun: Returns the complementary error function of a double.
erfcInverse(double) - Static method in class com.imsl.math.Sfun: Returns the inverse of the complementary error function.
error(String, Object[]) - Method in class com.imsl.chart.xml.ChartXML: Handles error messages.
error(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML: Receive notification of a recoverable error.
error(double[], double[]) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error: Returns the contribution to the error from a single training output target.
errorGradient(double[], double[]) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error: Returns the derivative of the error function with respect to the forecast output.
eval(HyperRectangleQuadrature.Function) - Method in class com.imsl.math.HyperRectangleQuadrature: Returns the value of the integral over the unit cube.
eval(HyperRectangleQuadrature.Function, double[], double[]) - Method in class com.imsl.math.HyperRectangleQuadrature: Returns the value of the integral over a cube.
eval(Quadrature.Function, double, double) - Method in class com.imsl.math.Quadrature: Returns the value of the integral from a to b.
eval(double, double) - Method in class com.imsl.stat.InverseCdf: Evaluates the inverse CDF function.
examineStep(int, double, double[]) - Method in class com.imsl.math.OdeRungeKutta: Called before and after each internal step.
excludeFirst(boolean) - Method in class com.imsl.stat.Difference: If set to true, the observations lost due to differencing will be excluded.
exp(Complex) - Static method in class com.imsl.math.Complex: Returns the exponential of a Complex z, exp(z).
exp(double) - Static method in class com.imsl.math.JMath: Returns the exponential of a double.
expectedNormalOrderStatistic(int, int) - Static method in class com.imsl.stat.Ranks: Returns the expected value of a normal order statistic.
expm1(double) - Static method in class com.imsl.math.Hyperbolic: Returns exp(x)-1, the exponential of x minus 1.
exponential(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the exponential cumulative probability distribution function.
exponentialProb(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the exponential probability density function
extrapolate(double) - Method in class com.imsl.math.EpsilonAlgorithm: Extrapolates the convergence limit of a sequence.
extremeValue(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the extreme value cumulative probability distribution function.
extremeValueProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the extreme value probability density function.

F

F(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the F cumulative probability distribution function.
FACE_XA - Static variable in class com.imsl.chart3d.AxisBox: Show the x = a face of the box.
FACE_XB - Static variable in class com.imsl.chart3d.AxisBox: Show the x = b face of the box.
FACE_YA - Static variable in class com.imsl.chart3d.AxisBox: Show the y = a face of the box.
FACE_YB - Static variable in class com.imsl.chart3d.AxisBox: Show the y = b face of the box.
FACE_ZA - Static variable in class com.imsl.chart3d.AxisBox: Show the z = a face of the box.
FACE_ZB - Static variable in class com.imsl.chart3d.AxisBox: Show the z = b face of the box.
FFT - class com.imsl.math.FFT.: FFT functions.
FFT(int) - Constructor for class com.imsl.math.FFT: Constructs an FFT object.
FILL - Static variable in class com.imsl.chart.Draw
FILL_TYPE_GRADIENT - Static variable in class com.imsl.chart.ChartNode: Value for attribute "FillType" indicating that the region is to be drawn in a color gradient as specified by the attribute Gradient.
FILL_TYPE_NONE - Static variable in class com.imsl.chart.ChartNode: Value for attribute "FillType" and "FillOutlineType" indicating that the region is not to be drawn.
FILL_TYPE_PAINT - Static variable in class com.imsl.chart.ChartNode: Value for attribute "FillType" indicating that the region is to be drawn using the texture specified by the attribute FillPaint.
FILL_TYPE_SOLID - Static variable in class com.imsl.chart.ChartNode: Value for attribute "FillType" and "FillOutlineType" indicating that the region is to be drawn using the solid color specified by the attribute FillColor or FillOutlineColor.
FIRST_DERIVATIVE - Static variable in class com.imsl.math.CsInterpolate
FORWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression: Indicates forward regression.
FProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the F probability density function.
FULL - Static variable in class com.imsl.math.PrintMatrix: This flag as the argument to setMatrixType, indicates that the full matrix is to be printed.
FactorAnalysis - class com.imsl.stat.FactorAnalysis.: Performs Principal Component Analysis or Factor Analysis on a covariance or correlation matrix.
FactorAnalysis(double[][], int, int) - Constructor for class com.imsl.stat.FactorAnalysis: Constructor for FactorAnalysis.
FactorAnalysis.BadVarianceException - exception com.imsl.stat.FactorAnalysis.BadVarianceException.: Bad variance error.
FactorAnalysis.BadVarianceException(String) - Constructor for class com.imsl.stat.FactorAnalysis.BadVarianceException
FactorAnalysis.BadVarianceException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.BadVarianceException
FactorAnalysis.EigenvalueException - exception com.imsl.stat.FactorAnalysis.EigenvalueException.: Eigenvalue error.
FactorAnalysis.EigenvalueException(String) - Constructor for class com.imsl.stat.FactorAnalysis.EigenvalueException
FactorAnalysis.EigenvalueException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.EigenvalueException
FactorAnalysis.NoDegreesOfFreedomException - exception com.imsl.stat.FactorAnalysis.NoDegreesOfFreedomException.: No degrees of freedom error.
FactorAnalysis.NoDegreesOfFreedomException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NoDegreesOfFreedomException
FactorAnalysis.NoDegreesOfFreedomException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NoDegreesOfFreedomException
FactorAnalysis.NonPositiveEigenvalueException - exception com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException.: Non positive eigenvalue error.
FactorAnalysis.NonPositiveEigenvalueException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException
FactorAnalysis.NonPositiveEigenvalueException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException
FactorAnalysis.NotPositiveDefiniteException - exception com.imsl.stat.FactorAnalysis.NotPositiveDefiniteException.: Covariance matrix not positive definite.
FactorAnalysis.NotPositiveDefiniteException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NotPositiveDefiniteException
FactorAnalysis.NotPositiveDefiniteException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NotPositiveDefiniteException
FactorAnalysis.NotPositiveSemiDefiniteException - exception com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException.: Covariance matrix not positive semi-definite.
FactorAnalysis.NotPositiveSemiDefiniteException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException
FactorAnalysis.NotPositiveSemiDefiniteException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException
FactorAnalysis.NotSemiDefiniteException - exception com.imsl.stat.FactorAnalysis.NotSemiDefiniteException.: Hessian matrix not semi-definite.
FactorAnalysis.NotSemiDefiniteException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NotSemiDefiniteException
FactorAnalysis.NotSemiDefiniteException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NotSemiDefiniteException
FactorAnalysis.RankException - exception com.imsl.stat.FactorAnalysis.RankException.: Rank of covariance matrix error.
FactorAnalysis.RankException(String) - Constructor for class com.imsl.stat.FactorAnalysis.RankException
FactorAnalysis.RankException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.RankException
FactorAnalysis.SingularException - exception com.imsl.stat.FactorAnalysis.SingularException.: Covariance matrix singular error.
FactorAnalysis.SingularException(String) - Constructor for class com.imsl.stat.FactorAnalysis.SingularException
FactorAnalysis.SingularException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.SingularException
FaureSequence - class com.imsl.stat.FaureSequence.: Generates the low-discrepancy Faure sequence.
FaureSequence(int) - Constructor for class com.imsl.stat.FaureSequence: Creates a Faure sequence with the default base.
FaureSequence(int, int, int) - Constructor for class com.imsl.stat.FaureSequence: Creates a Faure sequence.
FeedForwardNetwork - class com.imsl.datamining.neural.FeedForwardNetwork.: A representation of a feed forward neural network.
FeedForwardNetwork() - Constructor for class com.imsl.datamining.neural.FeedForwardNetwork: Creates a new instance of FeedForwardNetwork.
FillPaint - class com.imsl.chart.FillPaint.: A collection of methods to create Paint objects for fill areas.
Finance - class com.imsl.finance.Finance.: Collection of finance functions.
FlatFile - class com.imsl.io.FlatFile.: Reads a text file as a ResultSet.
FlatFile(BufferedReader, Tokenizer) - Constructor for class com.imsl.io.FlatFile: Creates a FlatFile from a BufferedReader.
FlatFile(BufferedReader) - Constructor for class com.imsl.io.FlatFile: Creates a FlatFile with the CSV tokenizer.
FlatFile(String) - Constructor for class com.imsl.io.FlatFile: Creates a FlatFile from a CSV file.
FlatFile(String, Tokenizer) - Constructor for class com.imsl.io.FlatFile: Creates a FlatFile from a file with the default tokenizer.
FlatFile.Parser - interface com.imsl.io.FlatFile.Parser.: Defines a method that parses a String into an Object.
f(double) - Method in interface com.imsl.chart.ChartFunction: Function to be charted.
f(double) - Method in class com.imsl.chart.ChartSpline: Function to be charted.
f(double, double) - Method in interface com.imsl.chart3d.Surface.ZFunction: Define the surface function.
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockObjective
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
f(double[]) - Method in interface com.imsl.math.HyperRectangleQuadrature.Function: Returns the value of the function at the given point.
f(double[]) - Method in interface com.imsl.math.MinConGenLin.Function: Public interface for the function to be minimized.
f(double[], int, boolean[]) - Method in interface com.imsl.math.MinConNLP.Function: Compute the value of the function at the given point.
f(int, int, double[], boolean[], double[]) - Method in interface com.imsl.math.MinConNonlin.Function: Deprecated. Returns the value of the function at the given point.
f(double) - Method in interface com.imsl.math.MinUncon.Function: Public interface for the smooth function of a single variable to be minimized.
f(double[]) - Method in interface com.imsl.math.MinUnconMultiVar.Function: Public interface for the multivariate function to be minimized.
f(double[], double[]) - Method in interface com.imsl.math.NonlinLeastSquares.Function: Public interface for the nonlinear least-squares function.
f(double, double[], double[]) - Method in interface com.imsl.math.OdeRungeKutta.Function: Returns the value of the function at the given point.
f(double) - Method in interface com.imsl.math.Quadrature.Function: Returns the value of the function at the given point.
f(double) - Method in interface com.imsl.math.RadialBasis.Function: A radial basis function.
f(double) - Method in class com.imsl.math.RadialBasis.Gaussian
f(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric
f(double) - Method in interface com.imsl.math.ZeroFunction.Function: Returns the value of the function at the given point.
f(double[], double[]) - Method in interface com.imsl.math.ZeroSystem.Function: Returns the value of the function at the given point.
f(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Function: Computes the weight, frequency, and residual given the parameter vector theta for a single observation.
fact(int) - Static method in class com.imsl.math.Sfun: Returns the factorial of an integer.
factor - Variable in class com.imsl.math.ComplexLU: LU factorization of A with partial pivoting
factor - Variable in class com.imsl.math.LU: LU factorization of A with partial pivoting
fatalError(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML: Receive notification of a non-recoverable error.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw: Fills a circular or elliptical arc covering the specified rectangle.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap: Fills a circular or elliptical arc covering the specified rectangle.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick: Fills a circular or elliptical arc covering the specified rectangle.
fillColor - Variable in class com.imsl.chart.Draw
fillOutlineColor - Variable in class com.imsl.chart.Draw
fillOutlineType - Variable in class com.imsl.chart.Draw
fillPaint - Variable in class com.imsl.chart.Draw
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.Draw: Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.Draw: Fill a polygon defined by a Polygon object.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawMap: Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.DrawMap: Fill a polygon defined by a Polygon object.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawPick: Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.DrawPick: Fill a polygon defined by a Polygon object.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.Draw: Fill a rectangle.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawMap: Fill a rectangle.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawPick: Fill a rectangle.
fillType - Variable in class com.imsl.chart.Draw
filter() - Method in class com.imsl.stat.KalmanFilter: Performs Kalman filtering and evaluates the likelihood function for the state-space model.
finalize() - Method in class com.imsl.chart.Chart
finalize() - Method in class com.imsl.chart3d.Chart3D
findColumn(String) - Method in class com.imsl.io.AbstractFlatFile: Maps the given ResultSet column name to its ResultSet column index.
findColumnName(int) - Method in class com.imsl.io.AbstractFlatFile: Maps the given columnIndex into its column name.
findLink(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the Link between two Nodes.
findLinks(Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns all of the Links to a given Node.
finite(double) - Static method in class com.imsl.math.IEEE: Finite number test on an argument of type double.
fire() - Method in class com.imsl.chart.DrawPick: Fires the pickListeners for all of the picked nodes.
firePickListeners(MouseEvent) - Method in class com.imsl.chart.ChartNode: Fires the pick listeners defined at this node and at all of its ancestors, if the event "hits" the node.
first() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the first row in this ResultSet object.
floatValue() - Method in class com.imsl.math.Complex: Returns the value of the real part as a float.
floatValue() - Method in class com.imsl.math.Physical: Returns the value of this dimensionless object.
floor(double) - Static method in class com.imsl.math.JMath: Returns the value of a double rounded toward negative infinity to an integral value.
forecast(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Computes a forecast using the Network.
forecast(double[]) - Method in class com.imsl.datamining.neural.Network: Returns a forecast for each of the Network's outputs computed from the trained Network.
forecast(int) - Method in class com.imsl.stat.ARMA: Computes forecasts and their associated probability limits for an ARMA model.
format(LogRecord) - Method in class com.imsl.math.MinConNLP.Formatter
format(int, Object, int, int, ParsePosition) - Method in class com.imsl.math.PrintMatrixFormat: Returns a formatted string.
formatLabel(double, double) - Method in class com.imsl.chart.Data
formatMessage(String, String, Object[]) - Static method in class com.imsl.Messages: A message is formatted using a MessageFormat string retrieved from the named resource bundle using the given key.
formatMessage(String, String) - Static method in class com.imsl.Messages: A message is formatted, without arguments, using a MessageFormat string retrieved from the named resource bundle using the given key.
forward(Complex[]) - Method in class com.imsl.math.ComplexFFT: Compute the Fourier coefficients of a complex periodic sequence.
forward(double[]) - Method in class com.imsl.math.FFT: Compute the Fourier coefficients of a real periodic sequence.
frobeniusNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Return the Frobenius norm of a Complex matrix.
frobeniusNorm(double[][]) - Static method in class com.imsl.math.Matrix: Return the Frobenius norm of a matrix.
fv(double, int, double, double, int) - Static method in class com.imsl.finance.Finance: Returns the future value of an investment.
fvschedule(double, double[]) - Static method in class com.imsl.finance.Finance: Returns the future value of an initial principal taking into consideration a schedule of compound interest rates.

G

GARCH - class com.imsl.stat.GARCH.: Computes estimates of the parameters of a GARCH(p,q) model.
GARCH(int, int, double[], double[]) - Constructor for class com.imsl.stat.GARCH: Constructor for GARCH.
GARCH.ConstrInconsistentException - exception com.imsl.stat.GARCH.ConstrInconsistentException.: The equality constraints are inconsistent.
GARCH.ConstrInconsistentException(String) - Constructor for class com.imsl.stat.GARCH.ConstrInconsistentException
GARCH.ConstrInconsistentException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.ConstrInconsistentException
GARCH.EqConstrInconsistentException - exception com.imsl.stat.GARCH.EqConstrInconsistentException.: The equality constraints and the bounds on the variables are found to be inconsistent.
GARCH.EqConstrInconsistentException(String) - Constructor for class com.imsl.stat.GARCH.EqConstrInconsistentException
GARCH.EqConstrInconsistentException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.EqConstrInconsistentException
GARCH.NoVectorXException - exception com.imsl.stat.GARCH.NoVectorXException.: No vector X satisfies all of the constraints.
GARCH.NoVectorXException(String) - Constructor for class com.imsl.stat.GARCH.NoVectorXException
GARCH.NoVectorXException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.NoVectorXException
GARCH.TooManyIterationsException - exception com.imsl.stat.GARCH.TooManyIterationsException.: Number of function evaluations exceeded 1000.
GARCH.TooManyIterationsException(String) - Constructor for class com.imsl.stat.GARCH.TooManyIterationsException
GARCH.TooManyIterationsException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.TooManyIterationsException
GARCH.VarsDeterminedException - exception com.imsl.stat.GARCH.VarsDeterminedException.: The variables are determined by the equality constraints.
GARCH.VarsDeterminedException(String) - Constructor for class com.imsl.stat.GARCH.VarsDeterminedException
GARCH.VarsDeterminedException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.VarsDeterminedException
GENERALIZED_LEAST_SQUARES - Static variable in class com.imsl.stat.FactorAnalysis: Indicates generalized least squares method.
GREEN - Static variable in interface com.imsl.chart.Colormap: Linear green colormap.
GREEN_PINK - Static variable in interface com.imsl.chart.Colormap: Green/pink colormap.
GREEN_RED_BLUE_WHITE - Static variable in interface com.imsl.chart.Colormap: Green/red/blue/white colormap.
GREEN_WHITE_EXPONENTIAL - Static variable in interface com.imsl.chart.Colormap: Exponential green/white colormap.
GREEN_WHITE_LINEAR - Static variable in interface com.imsl.chart.Colormap: Linear green/white colormap.
Grid - class com.imsl.chart.Grid.: Draws the grid lines perpendicular to an axis.
GridPolar - class com.imsl.chart.GridPolar.: Draws the grid lines for a polar plot.
g(double) - Method in interface com.imsl.datamining.neural.Activation: Returns the value of the activation function.
g(double) - Method in interface com.imsl.math.MinUncon.Derivative: Public interface for the smooth function of a single variable to be minimized.
g(double) - Method in interface com.imsl.math.RadialBasis.Function: The derivative of the radial basis function.
g(double) - Method in class com.imsl.math.RadialBasis.Gaussian
g(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric
gamma(double) - Static method in class com.imsl.math.Sfun: Returns the Gamma function of a double.
gamma(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the gamma cumulative probability distribution function.
gammaProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the gamma probability density function.
geometric(int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the discrete geometric cumulative probability distribution function.
geometricProb(int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the discrete geometric probability density function.
get(String) - Method in class com.imsl.chart.xml.ChartXML: Returns a generated object given the id attribute in the XML tag that created the object.
getALT() - Method in class com.imsl.chart.ChartNode: Returns the value of the "ALT" attribute.
getALT() - Method in class com.imsl.chart.DrawMap: Returns the current ALT string.
getANOVA() - Method in class com.imsl.math.RadialBasis: Returns the ANOVA statistics from the linear regression.
getANOVA() - Method in class com.imsl.stat.LinearRegression: Get an analysis of variance table and related statistics.
getANOVA() - Method in class com.imsl.stat.StepwiseRegression: Get an analysis of variance table and related statistics.
getANOVA() - Method in class com.imsl.stat.UserBasisRegression: Get an analysis of variance table and related statistics.
getANOVATable() - Method in class com.imsl.stat.ANOVAFactorial: Returns the analysis of variance table.
getAR() - Method in class com.imsl.stat.ARMA: Returns the final autoregressive parameter estimates.
getAR() - Method in class com.imsl.stat.GARCH: Returns the estimated values of autoregressive (AR) parameters.
getAbstractParent() - Method in class com.imsl.chart.AbstractChartNode: Returns the parent of this node.
getActivation() - Method in class com.imsl.datamining.neural.Perceptron: Returns the activation function.
getAdjustedRSquared() - Method in class com.imsl.stat.ANOVA: Returns the adjusted R-squared (in percent).
getAkaike() - Method in class com.imsl.stat.GARCH: Returns the value of Akaike Information Criterion evaluated at the estimated parameter array.
getAlignment() - Method in class com.imsl.chart.Text: Gets the alignment for this Text object.
getArray(int) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as an Array object in the Java programming language.
getArray(String) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as an Array object in the Java programming language.
getArray() - Method in class com.imsl.stat.ANOVA: Returns the ANOVA values as an array.
getAsciiStream(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.
getAsciiStream(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.
getAttribute(String) - Method in class com.imsl.chart.AbstractChartNode: Gets an attribute.
getAutoCorrelationX() - Method in class com.imsl.stat.CrossCorrelation: Returns the autocorrelations of the time series x.
getAutoCorrelationY() - Method in class com.imsl.stat.CrossCorrelation: Returns the autocorrelations of the time series y.
getAutoCorrelations() - Method in class com.imsl.stat.AutoCorrelation: Returns the autocorrelations of the time series x.
getAutoCovariance() - Method in class com.imsl.stat.ARMA: Returns the autocovariances of the time series z.
getAutoCovarianceX() - Method in class com.imsl.stat.CrossCorrelation: Returns the autocovariances of the time series x.
getAutoCovarianceY() - Method in class com.imsl.stat.CrossCorrelation: Returns the autocovariances of the time series y.
getAutoCovariances() - Method in class com.imsl.stat.AutoCorrelation: Returns the variance and autocovariances of the time series x.
getAutoscaleInput() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "AutoscaleInput" attribute.
getAutoscaleMinimumTimeInterval() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "AutoscaleMinimumTimeInterval" attribute.
getAutoscaleOutput() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "AutoscaleOutput" attribute.
getAxis() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Axis" attribute.
getAxisBox() - Method in class com.imsl.chart3d.AxisXYZ: Return the axis box node.
getAxisLabel() - Method in class com.imsl.chart.Axis1D: Returns the label node associated with this axis.
getAxisLabel() - Method in class com.imsl.chart3d.Axis3D: Returns the label node associated with this axis.
getAxisLine() - Method in class com.imsl.chart.Axis1D: Returns the axis line node associated with this axis.
getAxisLine() - Method in class com.imsl.chart3d.Axis3D: Returns the axis line node associated with this axis.
getAxisR() - Method in class com.imsl.chart.Polar: Return the radius axis node.
getAxisRLabel() - Method in class com.imsl.chart.AxisR: Returns the AxisRLabel node.
getAxisRLine() - Method in class com.imsl.chart.AxisR: Returns the AxisRLine node.
getAxisRMajorTick() - Method in class com.imsl.chart.AxisR: Returns the major tick node associated with this axis.
getAxisTheta() - Method in class com.imsl.chart.Polar: Return the angular axis node.
getAxisTitle() - Method in class com.imsl.chart.Axis1D: Returns the title node associated with this axis.
getAxisTitle() - Method in class com.imsl.chart3d.Axis3D: Returns the title node associated with this axis.
getAxisTitlePosition() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "AxisTitlePosition" attribute.
getAxisUnit() - Method in class com.imsl.chart.Axis1D: Returns the unit node associated with this axis.
getAxisX() - Method in class com.imsl.chart.AxisXY: Return the x-axis node.
getAxisX() - Method in class com.imsl.chart3d.AxisXYZ: Return the x-axis node.
getAxisY() - Method in class com.imsl.chart.AxisXY: Return the y-axis node.
getAxisY() - Method in class com.imsl.chart3d.AxisXYZ: Return the y-axis node.
getAxisZ() - Method in class com.imsl.chart3d.AxisXYZ: Return the z-axis node.
getBackground() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Background" attribute.
getBackground() - Method in class com.imsl.chart3d.Chart3D: Returns the value of the "Background" attribute.
getBalancedTable() - Method in class com.imsl.stat.TableMultiWay: Returns an object containing the balanced table.
getBarData() - Method in class com.imsl.chart.Bar: Returns the "BarData" attribute.
getBarGap() - Method in class com.imsl.chart.ChartNode: Returns the value of the "BarGap" attribute.
getBarItem() - Method in class com.imsl.chart.BarSet: Returns an array of BarItems.
getBarItem(int) - Method in class com.imsl.chart.BarSet: Returns the BarItem given the index.
getBarSet() - Method in class com.imsl.chart.Bar: Returns the BarSet object.
getBarSet(int, int) - Method in class com.imsl.chart.Bar: Returns the BarSet object.
getBarSet(int) - Method in class com.imsl.chart.Bar: Returns the BarSet object.
getBarType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "BarType" attribute.
getBarWidth() - Method in class com.imsl.chart.ChartNode: Returns the value of the "BarWidth" attribute.
getBase() - Method in class com.imsl.stat.FaureSequence: Returns the base.
getBias() - Method in class com.imsl.datamining.neural.Perceptron: Returns the bias for this perceptron.
getBigDecimal(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.
getBigDecimal(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.
getBinaryStream(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a binary stream of uninterpreted bytes.
getBinaryStream(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a stream of uninterpreted bytes.
getBlob(int) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.
getBlob(String) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.
getBlomScores(double[]) - Method in class com.imsl.stat.Ranks: Gets the Blom version of normal scores for each observation.
getBodies() - Method in class com.imsl.chart.BoxPlot: Returns a node containing the body elements in the Box plot.
getBoolean(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.
getBoolean(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.
getBooleanAttribute(String, boolean) - Method in class com.imsl.chart.AbstractChartNode: Convenience routine to get a Boolean-valued attribute.
getBoundingSphere() - Method in class com.imsl.chart3d.ChartNode3D: Gets the spherical bounding region object BoundingSphere.
getBounds() - Method in class com.imsl.datamining.neural.ScaleFilter: Retrieves bounds used during bounded scaling.
getBoxPlotType() - Method in class com.imsl.chart.BoxPlot: Returns the value of the "BoxPlotType" attribute.
getBreakpoints() - Method in class com.imsl.math.Spline: Returns a copy of the breakpoints.
getByte(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.
getByte(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.
getBytes(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.
getBytes(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.
getCDF() - Static method in class com.imsl.stat.KaplanMeierECDF: Retrieve CDF values up to, but not including the time values in x
getCanvas() - Method in class com.imsl.chart3d.Chart3D
getCanvas() - Method in class com.imsl.chart3d.JFrameChart3D: Returns the Canvas3DChart into which the chart is drawn.
getCaseAnalysis() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the case analysis.
getCaseStatistics(double[], double) - Method in class com.imsl.stat.LinearRegression: Returns the case statistics for an observation.
getCaseStatistics(double[], double, double) - Method in class com.imsl.stat.LinearRegression: Returns the case statistics for an observation and a weight.
getCaseStatistics(double[], double, int) - Method in class com.imsl.stat.LinearRegression: Returns the case statistics for an observation and future response count for the desired prediction interval.
getCaseStatistics(double[], double, double, int) - Method in class com.imsl.stat.LinearRegression: Returns the case statistics for an observation, weight, and future response count for the desired prediction interval.
getCellCounts() - Method in class com.imsl.stat.ChiSquaredTest: Returns the cell counts.
getCenter() - Method in class com.imsl.datamining.neural.ScaleFilter: Retrieves the measure of center to be used during z-score scaling.
getCharacterStream(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getCharacterStream(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getChart() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Chart" attribute.
getChart(HttpServletRequest) - Method in class com.imsl.chart.ChartServlet: Returns the chart found in the session saved with the key "chart"+id, where id is the value of the "id" parameter in the request.
getChart() - Method in class com.imsl.chart.JFrameChart: Return the Chart object.
getChart() - Method in class com.imsl.chart.JPanelChart: Return the Chart object.
getChart() - Method in class com.imsl.chart.xml.ChartXML: Returns the root node of the chart tree.
getChart3D() - Method in class com.imsl.chart3d.Canvas3DChart: Returns the Chart3D associated with this canvas.
getChart3D() - Method in class com.imsl.chart3d.JFrameChart3D: Return the Chart object.
getChartServletName() - Method in class com.imsl.chart.JspBean: Returns the URL of the servlet used to render the chart.
getChartTitle() - Method in class com.imsl.chart.ChartNode: Returns the value of the "ChartTitle" attribute.
getChiSquared() - Method in class com.imsl.stat.ChiSquaredTest: Returns the chi-squared statistic.
getChiSquared() - Method in class com.imsl.stat.ContingencyTable: Returns the Pearson chi-squared test statistic.
getChiSquared() - Method in class com.imsl.stat.NormalityTest: Returns the chi-square statistic for the chi-squared goodness-of-fit test.
getChiSquaredTest() - Method in class com.imsl.stat.NormOneSample: Returns the test statistic associated with the chi-squared test for variances.
getChiSquaredTest() - Method in class com.imsl.stat.NormTwoSample: Returns the test statistic associated with the chi-squared test for common, or pooled, variances.
getChiSquaredTestDF() - Method in class com.imsl.stat.NormOneSample: Returns the degrees of freedom associated with the chi-squared test for variances.
getChiSquaredTestDF() - Method in class com.imsl.stat.NormTwoSample: Returns the degrees of freedom associated with the chi-squared test for the common, or pooled, variances.
getChiSquaredTestP() - Method in class com.imsl.stat.NormOneSample: Returns the probability of a larger chi-squared associated with the chi-squared test for variances.
getChiSquaredTestP() - Method in class com.imsl.stat.NormTwoSample: Returns the probability of a larger chi-squared associated with the chi-squared test for common, or pooled, variances.
getChildList() - Method in class com.imsl.chart.AbstractChartNode: Returns the children of this node.
getChildren() - Method in class com.imsl.chart.ChartNode: Returns an array of the children of this node.
getChildren() - Method in class com.imsl.chart3d.ChartNode3D: Returns an array of the children of this node.
getClassMembership() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the group number to which the observation was classified.
getClassTable() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the classification table.
getClassificationVariableCounts() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the number of values taken by each classification variable.
getClassificationVariableValues() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the distinct values of the classification variables in ascending order.
getClipBounds() - Method in class com.imsl.chart.Draw: Get the clipping rectangle.
getClipData() - Method in class com.imsl.chart.ChartNode: Returns the value of the "ClipData" attribute.
getClob(int) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.
getClob(String) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.
getClose() - Method in class com.imsl.chart.HighLowClose: Gets the value of the attribute "Close".
getClusterCounts() - Method in class com.imsl.stat.ClusterKMeans: Returns the number of observations in each cluster.
getClusterLeftSons() - Method in class com.imsl.stat.ClusterHierarchical: Returns the left sons of each merged cluster.
getClusterLevel() - Method in class com.imsl.stat.ClusterHierarchical: Returns the level at which the clusters are joined.
getClusterMembership(int) - Method in class com.imsl.stat.ClusterHierarchical: Returns the cluster membership of each observation.
getClusterMembership() - Method in class com.imsl.stat.ClusterKMeans: Returns the cluster membership for each observation.
getClusterRightSons() - Method in class com.imsl.stat.ClusterHierarchical: Returns the right sons of each merged cluster.
getClusterSSQ() - Method in class com.imsl.stat.ClusterKMeans: Returns the within sum of squares for each cluster.
getCoefficient(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests: Returns the estimate for a coefficient.
getCoefficient(int) - Method in class com.imsl.stat.NonlinearRegression: Returns the estimate for a coefficient.
getCoefficient(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests: Returns the estimate for a coefficient of the independent variable.
getCoefficientOfVariation() - Method in class com.imsl.stat.ANOVA: Returns the coefficient of variation (in percent).
getCoefficientStatistics(int) - Method in class com.imsl.stat.SelectionRegression.Statistics: Returns the coefficients statistics for each of the best regressions found for each subset considered.
getCoefficientTTests() - Method in class com.imsl.stat.LinearRegression: Returns statistics relating to the regression coefficients.
getCoefficientTTests() - Method in class com.imsl.stat.StepwiseRegression: Returns the student-t test statistics for the regression coefficients.
getCoefficientVIF() - Method in class com.imsl.stat.StepwiseRegression: Returns the variance inflation factors for the final model in this invocation.
getCoefficients() - Method in class com.imsl.io.MPSReader.Row: Returns the coeffients of this row as a dense array.
getCoefficients() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the linear discriminant function coefficients.
getCoefficients() - Method in class com.imsl.stat.LinearRegression: Returns the regression coefficients.
getCoefficients() - Method in class com.imsl.stat.NonlinearRegression: Returns the regression coefficients.
getCoefficients() - Method in class com.imsl.stat.UserBasisRegression: Returns the regression coefficients.
getColorAttribute(String) - Method in class com.imsl.chart.AbstractChartNode: Convenience routine to get a Color-valued attribute.
getColorFunction() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "ColorFunction" attribute.
getColormap() - Method in class com.imsl.chart.Heatmap: Returns the value of the "Colormap" attribute.
getColumn() - Method in class com.imsl.io.MPSReader.Element: Returns the column index.
getColumnClass(int) - Method in class com.imsl.io.AbstractFlatFile: Returns the class of the items in the specified column.
getColumnCount() - Method in class com.imsl.io.AbstractFlatFile: Returns the number of columns in this ResultSet object.
getColumnCount() - Method in class com.imsl.io.FlatFile: Returns the number of columns in this ResultSet object.
getComponent() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Component" attribute.
getConcatenatedViewport() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Viewport" attribute concatenated with the "Viewport" attributes set in its ancestor nodes.
getConcatenatedViewport() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "Viewport" attribute concatenated with the "Viewport" attributes set in its ancestor nodes.
getConcurrency() - Method in class com.imsl.io.AbstractFlatFile: Returns the concurrency mode of this ResultSet object.
getConfidenceInterval() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the Confidence Interval on the mean for an observation.
getConstant() - Method in class com.imsl.stat.ARMA: Returns the constant parameter estimate.
getConstraintResiduals() - Method in class com.imsl.math.MinConNLP: Returns the constraint residuals.
getContingencyCoef() - Method in class com.imsl.stat.ContingencyTable: Returns contingency coefficient.
getContourLegend() - Method in class com.imsl.chart.Contour: Returns the contour chart legend.
getContourLevel() - Method in class com.imsl.chart.Contour: Returns all of the contour levels.
getContourLevel(int) - Method in class com.imsl.chart.Contour: Returns a ContourLevel.
getContributions() - Method in class com.imsl.stat.ContingencyTable: Returns the contributions to chi-squared for each cell in the table.
getCooksDistance() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns Cook's Distance for an observation.
getCoordinates() - Method in class com.imsl.chart.Dendrogram: Convenience routine to get the "Coordinates" attribute.
getCorrelations() - Method in class com.imsl.stat.FactorAnalysis: Returns the correlations of the principal components.
getCount() - Method in class com.imsl.stat.FaureSequence
getCovB() - Method in class com.imsl.stat.KalmanFilter: Returns the mean squared error matrix for b divided by sigma squared.
getCovV() - Method in class com.imsl.stat.KalmanFilter: Returns the variance-covariance matrix of v divided by sigma squared.
getCovariance() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the array of covariances.
getCovarianceMatrix() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the estimated asymptotic covariance matrix of the coefficients.
getCovariancesSwept() - Method in class com.imsl.stat.StepwiseRegression: Returns the results after cov has been swept for the columns corresponding to the variables in the model.
getCramersV() - Method in class com.imsl.stat.ContingencyTable: Returns Cramer's V.
getCreateImageMap() - Method in class com.imsl.chart.JspBean: Returns true if a client-side imagemap is to be created.
getCriterionOption() - Method in class com.imsl.stat.SelectionRegression: Returns the criterion option used to calculate the regression estimates.
getCriterionValues(int) - Method in class com.imsl.stat.SelectionRegression.Statistics: Returns an array containing the values of the best criterion for the number of variables considered.
getCross() - Method in class com.imsl.chart.AxisXY: Returns the value of the "Cross" attribute.
getCrossCorrelation() - Method in class com.imsl.stat.CrossCorrelation: Returns the cross-correlations between the time series x and y.
getCrossCorrelation() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the cross-correlations between the channels of x and y.
getCrossCovariance() - Method in class com.imsl.stat.CrossCorrelation: Returns the cross-covariances between the time series x and y.
getCrossCovariance() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the cross-covariances between the channels of x and y.
getCursorName() - Method in class com.imsl.io.AbstractFlatFile: Gets the name of the SQL cursor used by this ResultSet object.
getCustomMarkerFactory() - Method in class com.imsl.chart3d.Data: Returns a custom marker factory.
getCustomTransform() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "CustomTransform" attribute.
getCutpoints() - Method in class com.imsl.stat.ChiSquaredTest: Returns the cutpoints.
getDFError() - Method in class com.imsl.stat.NonlinearRegression: Returns the degrees of freedom for error.
getDFFITS() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns DFFITS for an observation.
getDataType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "DataType" attribute.
getDataType() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "DataType" attribute.
getDate(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDaysInYear(GregorianCalendar, GregorianCalendar) - Method in interface com.imsl.finance.BasisPart: Returns the number of days in the year.
getDegreesOfFreedom() - Method in class com.imsl.stat.ChiSquaredTest: Returns the degrees of freedom in chi-squared.
getDegreesOfFreedom() - Method in class com.imsl.stat.ContingencyTable: Returns the degrees of freedom for the chi-squared tests associated with the table.
getDegreesOfFreedom() - Method in class com.imsl.stat.NormalityTest: Returns the degrees of freedom for the chi-squared goodness-of-fit test.
getDegreesOfFreedomForError() - Method in class com.imsl.stat.ANOVA: Returns the degrees of freedom for error.
getDegreesOfFreedomForModel() - Method in class com.imsl.stat.ANOVA: Returns the degrees of freedom for model.
getDensity() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Density" attribute.
getDesignVariableMeans() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the means of the design variables.
getDeviations() - Method in class com.imsl.stat.ARMA: Returns the deviations from each forecast that give the confidence percent probability limits.
getDeviceMarkerSize() - Method in class com.imsl.chart.Draw: Returns the marker size in device corrdinates.
getDiffMean() - Method in class com.imsl.stat.NormTwoSample: Returns the difference in means, mean of x - mean of y.
getDimension() - Method in class com.imsl.stat.FaureSequence: Returns the dimension of the sequence.
getDimension() - Method in interface com.imsl.stat.RandomSequence: Returns the dimension of the sequence.
getDirection() - Method in class com.imsl.chart3d.DirectionalLight: Returns the value of the "Direction" attribute.
getDistanceMatrix() - Method in class com.imsl.stat.Dissimilarities: Returns the distance matrix.
getDouble(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.
getDouble(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.
getDoubleAttribute(String, double) - Method in class com.imsl.chart.AbstractChartNode: Convenience routine to get a Double-valued attribute.
getDoubleBuffering() - Method in class com.imsl.chart.ChartNode: Returns the value of the "DoubleBuffering" attribute.
getDown() - Method in class com.imsl.chart.Candlestick: Returns the CandlestickItem for down days.
getDual() - Method in class com.imsl.math.QuadraticProgramming: Returns the dual (Lagrange multipliers).
getDualSolution() - Method in class com.imsl.math.DenseLP: Returns the dual solution.
getDualSolution() - Method in class com.imsl.math.LinearProgramming: Returns the dual solution.
getDunnSidak(int, int) - Method in class com.imsl.stat.ANOVA: Computes the confidence interval of i-th mean - j-th mean, using the Dunn-Sidak method.
getEnumValue(String) - Static method in class com.imsl.chart.xml.ChartXML: Returns the int corresponding to an enumeration.
getEpochSize() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the number of sample training patterns in each stage 1 epoch.
getError() - Method in class com.imsl.datamining.neural.BinaryClassification: Returns the error function for use by QuasiNewtonTrainer for training a binary classification network.
getError() - Method in class com.imsl.datamining.neural.MultiClassification: Returns the error function for use by QuasiNewtonTrainer for training a classification network.
getError() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the function used to compute the error to be minimized.
getErrorEstimate() - Method in class com.imsl.math.EpsilonAlgorithm: Returns the current error estimate.
getErrorEstimate() - Method in class com.imsl.math.HyperRectangleQuadrature: Returns an estimate of the relative error in the computed result.
getErrorEstimate() - Method in class com.imsl.math.Quadrature: Returns an estimate of the relative error in the computed result.
getErrorGradient() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in interface com.imsl.datamining.neural.Trainer: Returns the value of the gradient of the error function with respect to the weights.
getErrorMeanSquare() - Method in class com.imsl.stat.ANOVA: Returns the error mean square.
getErrorNumber() - Method in class com.imsl.LicenseManagerException: Returns the FlexLM error number for this exception.
getErrorStatus() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the training error status.
getErrorStatus() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the error status from the trainer.
getErrorStatus() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the error status from the trainer.
getErrorStatus() - Method in interface com.imsl.datamining.neural.Trainer: Returns the error status.
getErrorStatus() - Method in class com.imsl.math.MinUnconMultiVar: Returns the non-fatal error status.
getErrorStatus() - Method in class com.imsl.math.NonlinLeastSquares: Get information about the performance of NonlinLeastSquares.
getErrorStatus() - Method in class com.imsl.math.Quadrature: Returns the non-fatal error status.
getErrorStatus() - Method in class com.imsl.stat.NonlinearRegression: Gets information about the performance of NonlinearRegression.
getErrorValue() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the value of the error function.
getErrorValue() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the final value of the error function.
getErrorValue() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the final value of the error function.
getErrorValue() - Method in interface com.imsl.datamining.neural.Trainer: Returns the value of the error function minimized by the trainer.
getExactMean() - Method in class com.imsl.stat.ContingencyTable: Returns exact mean.
getExactStdev() - Method in class com.imsl.stat.ContingencyTable: Returns exact standard deviation.
getExpectedCounts() - Method in class com.imsl.stat.ChiSquaredTest: Returns the expected counts.
getExpectedValues() - Method in class com.imsl.stat.ContingencyTable: Returns the expected values of each cell in the table.
getExplode() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Explode" attribute.
getExtendedLikelihoodObservations() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns a vector indicating which observations are included in the extended likelihood.
getF() - Method in class com.imsl.stat.ANOVA: Returns the F statistic.
getFTest() - Method in class com.imsl.stat.NormTwoSample: Returns the F test value of the F test for equality of variances.
getFTestDFdenominator() - Method in class com.imsl.stat.NormTwoSample: Returns the denominator degrees of freedom of the F test for equality of variances.
getFTestDFnumerator() - Method in class com.imsl.stat.NormTwoSample: Returns the numerator degrees of freedom of the F test for equality of variances.
getFTestP() - Method in class com.imsl.stat.NormTwoSample: Returns the probability of a larger F in absolute value for the F test for equality of variances, assuming equal variances.
getFactorLoadings() - Method in class com.imsl.stat.FactorAnalysis: Returns the unrotated factor loadings.
getFarMarkers() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the array of far markers.
getFarMarkers() - Method in class com.imsl.chart.BoxPlot: Returns the FarMarkers node.
getFeature() - Method in class com.imsl.LicenseManagerException: Returns the name of the feature that could not be licensed.
getFetchDirection() - Method in class com.imsl.io.AbstractFlatFile: Returns the fetch direction for this ResultSet object.
getFetchSize() - Method in class com.imsl.io.AbstractFlatFile: Returns the fetch size for this ResultSet object.
getFillColor() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "FillColor" attribute.
getFillOutlineColor() - Method in class com.imsl.chart.ChartNode: Returns the value of the "FillOutlineColor" attribute.
getFillOutlineType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "FillOutlineType" attribute.
getFillPaint() - Method in class com.imsl.chart.ChartNode: Returns the value of the "FillPaint" attribute.
getFillType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "FillType" attribute.
getFinalActiveConstraints() - Method in class com.imsl.math.MinConGenLin: Returns the indices of the final active constraints.
getFinalActiveConstraintsNum() - Method in class com.imsl.math.MinConGenLin: Returns the final number of active constraints.
getFirstTick() - Method in class com.imsl.chart.Axis1D: Convenience routine to get the "FirstTick" attribute.
getFirstTick() - Method in class com.imsl.chart3d.Axis3D: Convenience routine to get the "FirstTick" attribute.
getFloat(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.
getFloat(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.
getFont() - Method in class com.imsl.chart.AbstractChartNode: Convenience routine which gets a Font object based on the "FontName", "FontStyle" and "FontSize" attributes.
getFontName() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "FontName" attribute.
getFontSize() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "FontSize" attribute.
getFontStyle() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "FontStyle" attribute.
getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the derivatives of the outputs with respect to the weights.
getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.Network: Returns the derivatives of the outputs with respect to the weights.
getFormatter() - Static method in class com.imsl.datamining.neural.EpochTrainer: Returns the logging Formatter object.
getFormatter() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the logging Formatter object.
getFormatter() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the logging formatter object.
getFrequencyTable() - Method in class com.imsl.stat.TableOneWay: Returns the one-way frequency table.
getFrequencyTable(double, double) - Method in class com.imsl.stat.TableOneWay: Returns a one-way frequency table using known bounds.
getFrequencyTable() - Method in class com.imsl.stat.TableTwoWay: Returns the two-way frequency table.
getFrequencyTable(double, double, double, double) - Method in class com.imsl.stat.TableTwoWay: Compute a two-way frequency table using intervals of equal length and user supplied upper and lower bounds, xLowerBound, xUpperBound, yLowerBound, yUpperBound.
getFrequencyTableUsingClassmarks(double[]) - Method in class com.imsl.stat.TableOneWay: Returns the one-way frequency table using class marks.
getFrequencyTableUsingClassmarks(double[], double[]) - Method in class com.imsl.stat.TableTwoWay: Returns the two-way frequency table using either cutpoints or class marks.
getFrequencyTableUsingCutpoints(double[]) - Method in class com.imsl.stat.TableOneWay: Returns the one-way frequency table using cutpoints.
getFrequencyTableUsingCutpoints(double[], double[]) - Method in class com.imsl.stat.TableTwoWay: Returns the two-way frequency table using cutpoints.
getFrom() - Method in class com.imsl.datamining.neural.Link: Returns the origination Node for this Link.
getGSquared() - Method in class com.imsl.stat.ContingencyTable: Returns the likelihood ratio G² (chi-squared).
getGSquaredP() - Method in class com.imsl.stat.ContingencyTable: Returns the probability of a larger G² (chi-squared).
getGradient() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Gradient" attribute.
getGrid() - Method in class com.imsl.chart.Axis1D: Returns the grid node associated with this axis.
getGridPolar() - Method in class com.imsl.chart.Polar: Returns the grid.
getGroupCounts() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the group counts.
getGroupInformation() - Method in class com.imsl.stat.ANOVA: Returns information concerning the groups.
getGroups() - Method in class com.imsl.stat.TableMultiWay: Returns the number of observations (rows) in each group.
getHREF() - Method in class com.imsl.chart.ChartNode: Returns the value of the "HREF" attribute.
getHREF() - Method in class com.imsl.chart.DrawMap: Returns the current HREF string.
getHeatmapLabels() - Method in class com.imsl.chart.Heatmap: Returns the value of the "HeatmapLabels" attribute.
getHeatmapLegend() - Method in class com.imsl.chart.Heatmap: Returns the heatmap legend.
getHessian() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the Hessian computed at the initial parameter estimates.
getHiddenLayers() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the HiddenLayers in this network.
getHigh() - Method in class com.imsl.chart.ErrorBar: Convenience routine to get the "High" attribute.
getHigh() - Method in class com.imsl.chart.HighLowClose: Convenience routine to get the "High" attribute.
getHistory() - Method in class com.imsl.stat.StepwiseRegression: Returns the stepwise regression history for the independent variables.
getId() - Method in class com.imsl.chart.JspBean: Returns the identifier number for the chart.
getImage() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Image" attribute.
getImageMap() - Method in class com.imsl.chart.JspBean: Returns an HTML for the client-side imagemap.
getImageTag() - Method in class com.imsl.chart.JspBean: Returns an HTML image tag.
getIncidenceMatrix() - Method in class com.imsl.stat.Covariances: Returns the incidence matrix.
getIndependentVariables(int) - Method in class com.imsl.stat.SelectionRegression.Statistics: Returns the identification numbers for the independent variables for the number of variables considered and in the same order as the criteria returned by SelectionRegression.Statistics.getCriterionValues(int).
getIndex() - Method in class com.imsl.datamining.neural.Layer: Returns the index of this Layer.
getInfo() - Method in class com.imsl.math.SVD: Returns convergence information about S, U, and V.
getInputLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the InputLayer.
getInputLayer() - Method in class com.imsl.datamining.neural.Network: Returns the InputLayer object.
getInt(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.
getInt(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.
getIntegerAttribute(String, int) - Method in class com.imsl.chart.AbstractChartNode: Convenience routine to get an Integer-valued attribute.
getIterationCount() - Method in class com.imsl.math.DenseLP: Returns the iteration count.
getIterations() - Method in class com.imsl.math.MinConNLP: Returns the actual number of iterations used.
getIterations() - Method in class com.imsl.math.MinUnconMultiVar: Returns the number of iterations used to compute a minimum.
getIterations(int) - Method in class com.imsl.math.ZeroFunction: Returns the number of iterations used to compute a root.
getJackknifeResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the Jackknife Residual for an observation.
getJacobian() - Method in class com.imsl.math.BoundedLeastSquares: Returns the Jacobian at the approximate solution.
getKeyboard() - Method in class com.imsl.chart3d.Chart3D: Returns the value of the "Keyboard" attribute.
getKnots() - Method in class com.imsl.math.BSpline: Returns a copy of the knot sequence.
getKurtosis() - Method in class com.imsl.stat.Summary: Returns the kurtosis.
getLabelType() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "LabelType" attribute.
getLabels() - Method in class com.imsl.chart.AxisLabel: Returns the "Labels" attribute.
getLabels() - Method in class com.imsl.chart.AxisRLabel: Returns the "Labels" attribute.
getLabels() - Method in class com.imsl.chart3d.AxisLabel: Returns the "Labels" attribute.
getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConGenLin: Returns the Lagrange multiplier estimates of the final active constraints.
getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConNLP: Returns the Lagrange multiplier estimates of the constraints.
getLastParameterUpdates() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the last parameter updates (excluding step halvings).
getLayer() - Method in class com.imsl.datamining.neural.Node: Returns the Layer in which this Node exists.
getLeftSons() - Method in class com.imsl.chart.Dendrogram: Convenience routine to get the "LeftSons" attribute.
getLegend() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Legend" attribute.
getLevels() - Method in class com.imsl.chart.Dendrogram: Convenience routine to get the "Levels" attribute.
getLeverage() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the Leverage for an observation.
getLicensePath() - Method in class com.imsl.LicenseManagerException: Returns the license file path for this exception.
getLightColor() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "LightColor" attribute.
getLineColor() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "LineColor" attribute.
getLineDashPattern() - Method in class com.imsl.chart.ChartNode: Returns the value of the "LineDashPattern" attribute.
getLineWidth() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "LineWidth" attribute.
getLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Return all of the Links in this Network.
getLinks() - Method in class com.imsl.datamining.neural.Network: Returns an array containing the Link objects in the Network.
getListCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable: Returns for each row, a list of the levels of nKeys corresponding classification variables that describe a cell.
getLocale() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Locale" attribute.
getLocalizedMessage() - Method in class com.imsl.LicenseManagerException: Returns the localized error message for this exception.
getLogDeterminant() - Method in class com.imsl.stat.KalmanFilter: Returns the natural log of the product of the nonzero eigenvalues of P where P * sigma² is the variance-covariance matrix of the observations.
getLogLikelihood() - Method in class com.imsl.stat.GARCH: Returns the value of Log-likelihood function evaluated at the estimated parameter array.
getLogger() - Static method in class com.imsl.datamining.neural.EpochTrainer: Returns the Logger object.
getLogger() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the Logger object.
getLogger() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the Logger object.
getLogger() - Method in class com.imsl.math.MinConNLP: Returns the logger object.
getLong(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.
getLong(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.
getLow() - Method in class com.imsl.chart.ErrorBar: Convenience routine to get the "Low" attribute.
getLow() - Method in class com.imsl.chart.HighLowClose: Convenience routine to get the "Low" attribute.
getLowerAdjacentValue() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the lower adjacent value.
getLowerBound(int) - Method in class com.imsl.io.MPSReader: Returns the lower bound for a variable.
getLowerCICommonVariance() - Method in class com.imsl.stat.NormTwoSample: Returns the lower confidence limits for the common, or pooled, variance.
getLowerCIDiff() - Method in class com.imsl.stat.NormTwoSample: Returns the lower confidence limit for the mean of the first population minus the mean of the second for equal or unequal variances depending on the value set by setUnequalVariances.
getLowerCIMean() - Method in class com.imsl.stat.NormOneSample: Returns the lower confidence limit for the mean.
getLowerCIRatioVariance() - Method in class com.imsl.stat.NormTwoSample: Returns the approximate lower confidence limit for the ratio of the variance of the first population to the second.
getLowerCIVariance() - Method in class com.imsl.stat.NormOneSample: Returns the lower confidence limits for the variance.
getLowerQuartile() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the lower quartile value.
getLowerRange(int) - Method in class com.imsl.io.MPSReader: Returns the lower range value for a constraint equation.
getMA() - Method in class com.imsl.stat.ARMA: Returns the final moving average parameter estimates.
getMA() - Method in class com.imsl.stat.GARCH: Returns the estimated values of moving average (MA) parameters.
getMahalanobis() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the Mahalanobis distances between the group means.
getMajorTick() - Method in class com.imsl.chart.Axis1D: Returns the major tick node associated with this axis.
getMajorTick() - Method in class com.imsl.chart3d.Axis3D: Returns the major tick node associated with this axis.
getMap() - Method in class com.imsl.chart.DrawMap: Returns the body of the HTML imagemap.
getMapName() - Method in class com.imsl.chart.JspBean: Returns the name of the client-size imagemap.
getMarkerColor() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "MarkerColor" attribute.
getMarkerDashPattern() - Method in class com.imsl.chart.ChartNode: Returns the value of the "MarkerPattern" attribute.
getMarkerPulsingCycle() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerPulsingCycle" attribute.
getMarkerPulsingCycleOffset() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerPulsingCycleOffset" attribute.
getMarkerPulsingMaximumScale() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerPulsingMaximumScale" attribute.
getMarkerPulsingMinimumScale() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerPulsingMinimumScale" attribute.
getMarkerRotatingAxis() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerRotatingAxis" attribute.
getMarkerRotatingCycle() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerRotatingCycle" attribute.
getMarkerRotatingCycleOffset() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerRotatingCycleOffset" attribute.
getMarkerSize() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "MarkerSize" attribute.
getMarkerThickness() - Method in class com.imsl.chart.ChartNode: Returns the value of the "MarkerThickness" attribute.
getMarkerType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "MarkerType" attribute.
getMarkerType() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerType" attribute.
getMaterial() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "Material" attribute.
getMaxDifference() - Method in class com.imsl.stat.NormalityTest: Returns the maximum absolute difference between the empirical and the theoretical distributions for the Lilliefors test.
getMaximum() - Method in class com.imsl.stat.Summary: Returns the maximum.
getMaximum() - Method in class com.imsl.stat.TableOneWay: Returns maximum value of x.
getMaximumTime() - Method in class com.imsl.math.MinConNLP: Returns the maximum time allowed for the solve step.
getMaximumValue() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the maximum value of the observations.
getMaximumX() - Method in class com.imsl.stat.TableTwoWay: Returns the maximum value of x.
getMaximumY() - Method in class com.imsl.stat.TableTwoWay: Returns the maximum value of y.
getMean() - Method in class com.imsl.stat.AutoCorrelation: Returns the mean of the time series x.
getMean() - Method in class com.imsl.stat.NormOneSample: Returns the mean of the sample.
getMean() - Method in class com.imsl.stat.Summary: Returns the population mean.
getMeanEstimate() - Method in class com.imsl.stat.ARMA: Returns an update of the mean of the time series z.
getMeanOfY() - Method in class com.imsl.stat.ANOVA: Returns the mean of the response (dependent variable).
getMeanX() - Method in class com.imsl.stat.CrossCorrelation: Returns the mean of the time series x.
getMeanX() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the mean of each channel of x.
getMeanX() - Method in class com.imsl.stat.NormTwoSample: Returns the mean of the first sample, x.
getMeanY() - Method in class com.imsl.stat.CrossCorrelation: Returns the mean of the time series y.
getMeanY() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the mean of each channel of y.
getMeanY() - Method in class com.imsl.stat.NormTwoSample: Returns the mean of the second sample, y.
getMeans() - Method in class com.imsl.stat.ANOVAFactorial: Returns the subgroup means.
getMeans() - Method in class com.imsl.stat.Covariances: Returns the means of the variables in x.
getMeans() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the variable means.
getMedian() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the median value.
getMedianLowerConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the lower confidence interval for the median.
getMedianUpperConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the upper confidence interval for the median.
getMetaData() - Method in class com.imsl.io.AbstractFlatFile: Retrieves the number, types and properties of this ResultSet object's columns.
getMinimum() - Method in class com.imsl.stat.Summary: Returns the minimum.
getMinimum() - Method in class com.imsl.stat.TableOneWay: Returns the minimum value of x.
getMinimumValue() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the minimum value of the observations.
getMinimumX() - Method in class com.imsl.stat.TableTwoWay: Returns the minimum value of x.
getMinimumY() - Method in class com.imsl.stat.TableTwoWay: Returns the minimum value of y.
getMinorTick() - Method in class com.imsl.chart.Axis1D: Returns the minor tick node associated with this axis.
getModelErrorStdev() - Method in class com.imsl.stat.ANOVA: Returns the estimated standard deviation of the model error.
getModelMeanSquare() - Method in class com.imsl.stat.ANOVA: Returns the model mean square.
getMonthBasis() - Method in class com.imsl.finance.DayCountBasis: Returns the (days in month) portion of the Day Count Basis.
getNCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable: Returns the number of non-empty cells.
getNRowsMissing() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the number of rows of data in x that contain missing values in one or more specific columns of x.
getNRowsMissing() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the number of rows of data encountered containing missing values (NaN).
getNTimes() - Static method in class com.imsl.stat.KaplanMeierECDF: Retrieves the number of points in the empirical CDF
getName() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Name" attribute.
getName() - Method in class com.imsl.io.MPSReader.Row: Returns the name of this row.
getName() - Method in class com.imsl.io.MPSReader: Returns the name of the MPS problem.
getNameBounds() - Method in class com.imsl.io.MPSReader: Returns the name of the BOUNDS set.
getNameColumn(int) - Method in class com.imsl.io.MPSReader: Returns the name of a constraint column.
getNameObjective() - Method in class com.imsl.io.MPSReader: Returns the name of the free row containing the objective.
getNameRHS() - Method in class com.imsl.io.MPSReader: Returns the name of the RHS section.
getNameRanges() - Method in class com.imsl.io.MPSReader: Returns the name of the RANGES set.
getNameRow(int) - Method in class com.imsl.io.MPSReader: Returns the name of a contraint row.
getNetwork() - Method in class com.imsl.datamining.neural.BinaryClassification: Returns the network being used for classification.
getNetwork() - Method in class com.imsl.datamining.neural.MultiClassification: Returns the network being used for classification.
getNode() - Method in class com.imsl.chart.PickEvent: Gets this ChartNode.
getNodes() - Method in class com.imsl.datamining.neural.InputLayer: Return the Perceptrons in the InputLayer.
getNodes() - Method in class com.imsl.datamining.neural.Layer: Return a list of the Perceptrons in this Layer.
getNodes() - Method in class com.imsl.datamining.neural.OutputLayer: Return the Perceptrons in the OutputLayer.
getNormalScores(double[]) - Method in class com.imsl.stat.Ranks: Gets the expected value of normal order statistics (for tied observations, the average of the expected normal scores).
getNotch() - Method in class com.imsl.chart.BoxPlot: Gets the "Notch" attribute value.
getNumPositiveDev() - Method in class com.imsl.stat.SignTest: Returns the number of positive differences.
getNumRowMissing() - Method in class com.imsl.stat.Covariances: Returns the total number of observations that contain any missing values (Double.NaN).
getNumZeroDev() - Method in class com.imsl.stat.SignTest: Returns the number of zero differences.
getNumber() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Number" attribute.
getNumberFormat() - Method in class com.imsl.math.PrintMatrixFormat: Returns the NumberFormat to be used in formatting double and Complex entries.
getNumberGridPointsX() - Method in class com.imsl.chart3d.Surface: Returns the value of the "NumberGridPointsX" attribute.
getNumberGridPointsY() - Method in class com.imsl.chart3d.Surface: Returns the value of the "NumberGridPointsY" attribute.
getNumberObservations() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the number of observations.
getNumberOfBinaryConstraints() - Method in class com.imsl.io.MPSReader: Returns the number of binary constraints.
getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Retrieves the number of classes in the nominal variable.
getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Retrieves the number of categories associated with this ordinal variable.
getNumberOfColumns() - Method in class com.imsl.io.MPSReader: Returns the number of columns in the constraint matrix.
getNumberOfEpochs() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the number of epochs used during stage I training.
getNumberOfInputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the number of inputs to the Network.
getNumberOfInputs() - Method in class com.imsl.datamining.neural.Network: Returns the number of Network inputs.
getNumberOfIntegerConstraints() - Method in class com.imsl.io.MPSReader: Returns the number of integer constraints.
getNumberOfLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the number of Links in the Network.
getNumberOfLinks() - Method in class com.imsl.datamining.neural.Network: Returns the number of Network Links among the nodes.
getNumberOfNonZeros() - Method in class com.imsl.io.MPSReader.Row: Returns the number of nonzero elements in this row.
getNumberOfNonZeros() - Method in class com.imsl.io.MPSReader: Returns the number of nonzeros in the constraint matrix.
getNumberOfOutputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the number of outputs from the Network.
getNumberOfOutputs() - Method in class com.imsl.datamining.neural.Network: Returns the number of Network output Perceptrons.
getNumberOfRows() - Method in class com.imsl.io.MPSReader: Returns the number of rows in the constraint matrix.
getNumberOfThreads() - Method in class com.imsl.datamining.neural.EpochTrainer: Gets the number of threads to use during stage I training.
getNumberOfWeights() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the number of weights in the Network.
getNumberOfWeights() - Method in class com.imsl.datamining.neural.Network: Returns the number of weights in the Network.
getNvalues() - Method in class com.imsl.stat.TableMultiWay.BalancedTable: Returns an array of length nKeys containing in its i-th element (i=0,1,...nKeys-1), the number of levels or categories of the i-th classification variable (column).
getObject(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(int, Map) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(String, Map) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(int) - Method in class com.imsl.io.FlatFile: Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObjective() - Method in class com.imsl.io.MPSReader: Returns the objective as a Row.
getObjectiveCoefficients() - Method in class com.imsl.io.MPSReader: Returns the coefficents of the objective row.
getObjectiveValue() - Method in class com.imsl.math.MinConGenLin: Returns the value of the objective function.
getObsPerCluster(int) - Method in class com.imsl.stat.ClusterHierarchical: Returns the number of observations in each cluster.
getObservations() - Method in class com.imsl.stat.Covariances: Returns the sum of the frequencies.
getObservationsLost() - Method in class com.imsl.stat.Difference: Returns the number of observations lost because of differencing the time series.
getObservedResponse() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the observed response for an observation.
getOffset() - Method in class com.imsl.chart.Text: Returns the offset.
getOpen() - Method in class com.imsl.chart.HighLowClose: Gets the value of the attribute "Open".
getOptimalValue() - Method in class com.imsl.math.DenseLP: Returns the optimal value of the objective function.
getOptimalValue() - Method in class com.imsl.math.LinearProgramming: Returns the optimal value of the objective function.
getOptimizedCriterion() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the optimized criterion.
getOrbit() - Method in class com.imsl.chart3d.Chart3D: Returns the value of the "Orbit" attribute.
getOrder() - Method in class com.imsl.chart.Dendrogram: Convenience routine to get the "Order" attribute.
getOutputLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the OutputLayer.
getOutputLayer() - Method in class com.imsl.datamining.neural.Network: Returns the OutputLayer.
getOutsideMarkers() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the array of outside markers.
getOutsideMarkers() - Method in class com.imsl.chart.BoxPlot: Returns the OutsideMarkers node.
getP() - Method in class com.imsl.stat.ANOVA: Returns the p-value.
getP() - Method in class com.imsl.stat.ChiSquaredTest: Returns the p-value for the chi-squared statistic.
getP() - Method in class com.imsl.stat.ContingencyTable: Returns the Pearson chi-squared p-value for independence of rows and columns.
getPValue(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests: Returns the p-value for the two-sided test.
getPValue(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests: Returns the p-value for the two-sided test $H_0 : { beta} = 0$ vs.
getPaint() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Paint" attribute.
getPanel() - Method in class com.imsl.chart.JFrameChart: Returns the JPanelChart into which the chart is drawn.
getParamEstimatesCovariance() - Method in class com.imsl.stat.ARMA: Returns the covariances of parameter estimates.
getParameterUpdates() - Method in class com.imsl.stat.FactorAnalysis: Returns the parameter updates.
getParameters() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the parameter estimates and associated statistics.
getParent() - Method in class com.imsl.chart.ChartNode: Returns the parent of this node.
getParent() - Method in class com.imsl.chart3d.ChartNode3D: Returns the parent of this node.
getPartialAutoCorrelations() - Method in class com.imsl.stat.AutoCorrelation: Returns the sample partial autocorrelation function of the stationary time series x.
getPercentages() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Retrieves the cumulative percentages used for encoding and decoding.
getPercents() - Method in class com.imsl.stat.FactorAnalysis: Returns the cumulative percent of the total variance explained by each principal component.
getPerceptrons() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the Perceptrons in this Network.
getPerceptrons() - Method in class com.imsl.datamining.neural.Network: Returns an array containing the Perceptrons in the Network.
getPermute() - Method in class com.imsl.math.QR: Returns an integer vector containing information about the permutation of the elements of the matrix during pivoting.
getPhi() - Method in class com.imsl.stat.ContingencyTable: Returns phi.
getPieSlice() - Method in class com.imsl.chart.Pie: Returns the PieSlice objects.
getPieSlice(int) - Method in class com.imsl.chart.Pie: Returns a specified PieSlice.
getPooledVariance() - Method in class com.imsl.stat.NormTwoSample: Returns the Pooled variance for the two samples.
getPosition() - Method in class com.imsl.chart3d.ColormapLegend: Returns the position of the legend.
getPosition() - Method in class com.imsl.chart3d.PointLight: Returns the value of the "Position" attribute.
getPredictedResponse() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the predicted response for an observation.
getPredictionError() - Method in class com.imsl.stat.KalmanFilter: Returns the one-step-ahead prediction error.
getPredictionInterval() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the Prediction Interval for an observation.
getPrimalSolution() - Method in class com.imsl.math.DenseLP: Returns the solution x of the linear programming problem.
getPrimalSolution() - Method in class com.imsl.math.LinearProgramming: Returns the solution x of the linear programming problem.
getPrior() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the prior probabilities.
getProbability() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the posterior probabilities for each observation.
getProduct() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the inverse of the Hessian times the gradient vector computed at the input parameter estimates.
getPsiWeights() - Method in class com.imsl.stat.ARMA: Returns the psi weights of the infinite order moving average form of the model.
getQ() - Method in class com.imsl.math.QR: Returns the orthogonal or unitary matrix Q.
getQ() - Method in class com.imsl.stat.EmpiricalQuantiles: Returns the empirical quantiles.
getR() - Method in class com.imsl.math.Cholesky: Returns the R matrix that results from the Cholesky factorization.
getR() - Method in class com.imsl.math.QR: Returns the upper trapezoidal matrix R.
getR() - Method in class com.imsl.stat.LinearRegression: Returns a copy of the R matrix.
getR() - Method in class com.imsl.stat.NonlinearRegression: Returns a copy of the R matrix.
getRSquared() - Method in class com.imsl.stat.ANOVA: Returns the R-squared (in percent).
getRadialFunction() - Method in class com.imsl.math.RadialBasis: Returns the radial function.
getRadius(int) - Method in class com.imsl.math.ZeroPolynomial: Returns an a-posteriori absolute error bound on the root.
getRandom() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the random number generator used to perturb the stage 1 guesses.
getRandomSampleIndicies() - Method in class com.imsl.datamining.neural.EpochTrainer: Gets the random number generators used to select random training patterns in stage 1.
getRank() - Method in class com.imsl.math.QR: Returns the rank of the matrix used to construct this instance.
getRank() - Method in class com.imsl.math.SVD: Returns the rank of the matrix used to construct this instance.
getRank() - Method in class com.imsl.stat.KalmanFilter: Returns the rank of the variance-covariance matrix for all the observations.
getRank() - Method in class com.imsl.stat.LinearRegression: Returns the rank of the matrix.
getRank() - Method in class com.imsl.stat.NonlinearRegression: Returns the rank of the matrix.
getRanks(double[]) - Method in class com.imsl.stat.Ranks: Gets the rank for each observation.
getRef(int) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Ref object in the Java programming language.
getRef(String) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Ref object in the Java programming language.
getReference() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Reference" attribute.
getResidual() - Method in class com.imsl.stat.ARMA: Returns the residuals.
getResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the Residual for an observation.
getResiduals() - Method in class com.imsl.math.BoundedLeastSquares: Returns the residuals at the approximate solution.
getRightSons() - Method in class com.imsl.chart.Dendrogram: Convenience routine to get the "RightSons" attribute.
getRoot(int) - Method in class com.imsl.math.ZeroPolynomial: Returns a zero of the polynomial.
getRoots() - Method in class com.imsl.math.ZeroPolynomial: Returns the zeros of the polynomial.
getRow() - Method in class com.imsl.io.AbstractFlatFile: Retrieves the current row number.
getRow(int) - Method in class com.imsl.io.MPSReader: Returns a row of the constraint matrix or a free row.
getRowCoefficients(int) - Method in class com.imsl.io.MPSReader: Returns the coefficents of a row.
getS() - Method in class com.imsl.math.SVD: Returns the singular values.
getSSE() - Method in class com.imsl.stat.NonlinearRegression: Returns the sums of squares for error.
getSSResidual() - Method in class com.imsl.stat.ARMA: Returns the sum of squares of the random shock.
getSampleStandardDeviation() - Method in class com.imsl.stat.Summary: Returns the sample standard deviation.
getSampleVariance() - Method in class com.imsl.stat.Summary: Returns the sample variance.
getSavageScores(double[]) - Method in class com.imsl.stat.Ranks: Gets the Savage scores (the expected value of exponential order statistics).
getScaleFont() - Method in class com.imsl.chart.Draw: Returns the factor by which fonts are to be scaled.
getScreenAxis() - Method in class com.imsl.chart.ChartNode: Returns the value of the "ScreenAxis" attribute.
getScreenSize() - Method in class com.imsl.chart.ChartNode: Returns the value of the "ScreenSize" attribute.
getScreenViewport() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Viewport" attribute scaled by the screen size.
getShapiroWilkW() - Method in class com.imsl.stat.NormalityTest: Returns the Shapiro-Wilk W statistic for the Shapiro-Wilk W test.
getShort(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a short in the Java programming language.
getShort(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a short in the Java programming language.
getSigma() - Method in class com.imsl.stat.GARCH: Returns the estimated value of sigma squared.
getSize() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Size" attribute.
getSize(Text) - Method in class com.imsl.chart.Draw: Returns the size of the bounding box for a text object.
getSize() - Method in class com.imsl.chart.JspBean: Returns the size of the generated image.
getSkewness() - Method in class com.imsl.stat.Summary: Returns the skewness.
getSkip() - Method in class com.imsl.stat.FaureSequence: Returns the number of points skipped at the beginning of the sequence.
getSkipWeekends() - Method in class com.imsl.chart.ChartNode: Returns the value of the "SkipWeekends" attribute.
getSolution() - Method in class com.imsl.math.BoundedLeastSquares: Returns the solution.
getSolution() - Method in class com.imsl.math.MinConGenLin: Returns the computed solution.
getSolution() - Method in class com.imsl.math.MinConNLP: Returns the solution.
getSolution() - Method in class com.imsl.math.QuadraticProgramming: Returns the solution.
getSpline() - Method in class com.imsl.math.BSpline: Returns a Spline representation of the B-spline.
getSpread() - Method in class com.imsl.datamining.neural.ScaleFilter: Retrieves the measure of spread to be used during scaling.
getStage1Trainer() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the stage 1 trainer.
getStage2Trainer() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the stage 1 trainer.
getStandardDeviation() - Method in class com.imsl.stat.Summary: Returns the population standard deviation.
getStandardError(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests: Returns the estimated standard error for a coefficient estimate.
getStandardError(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests: Returns the estimated standard error for a coefficient estimate.
getStandardErrors(int) - Method in class com.imsl.stat.AutoCorrelation: Returns the standard errors of the autocorrelations of the time series x.
getStandardErrors(int) - Method in class com.imsl.stat.CrossCorrelation: Returns the standard errors of the cross-correlations between the time series x and y.
getStandardErrors() - Method in class com.imsl.stat.FactorAnalysis: Returns the estimated asymptotic standard errors of the eigenvalues.
getStandardizedResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the Standardized Residual for an observation.
getStateVector() - Method in class com.imsl.stat.KalmanFilter: Returns the estimated state vector at time k + 1 given the observations through time k.
getStatement() - Method in class com.imsl.io.AbstractFlatFile: Returns the Statement object that produced this ResultSet object.
getStatistics() - Method in class com.imsl.chart.BoxPlot: Returns an array of BoxPlot.Statistics objects, one for each set of observations.
getStatistics(int) - Method in class com.imsl.chart.BoxPlot: Returns a BoxPlot.Statistics for a set of observations.
getStatistics() - Method in class com.imsl.stat.ContingencyTable: Returns the statistics associated with this table.
getStatistics() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns statistics.
getStatistics() - Method in class com.imsl.stat.FactorAnalysis: Returns statistics.
getStatistics() - Method in class com.imsl.stat.SelectionRegression: Returns a new Statistics object.
getStatistics() - Method in class com.imsl.stat.WilcoxonRankSum: Returns the statistics.
getStatus(int) - Method in class com.imsl.math.ZeroPolynomial: Returns the error status of a root.
getStdDev() - Method in class com.imsl.stat.NormOneSample: Returns the standard deviation of the sample.
getStdDevX() - Method in class com.imsl.stat.NormTwoSample: Returns the standard deviation of the first sample.
getStdDevY() - Method in class com.imsl.stat.NormTwoSample: Returns the standard deviation of the second sample.
getString() - Method in class com.imsl.chart.Text: Gets the string for this Text object.
getString(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.
getString(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.
getStringAttribute(String) - Method in class com.imsl.chart.AbstractChartNode: Convenience routine to get a String-valued attribute.
getSumOfSquares() - Method in class com.imsl.stat.KalmanFilter: Returns the generalized sum of squares.
getSumOfSquaresForError() - Method in class com.imsl.stat.ANOVA: Returns the sum of squares for error.
getSumOfSquaresForModel() - Method in class com.imsl.stat.ANOVA: Returns the sum of squares for model.
getSumOfWeights() - Method in class com.imsl.stat.Covariances: Returns the sum of the weights of all observations.
getSurfaceType() - Method in class com.imsl.chart3d.Surface: Returns the attribute "SurfaceType".
getSwept() - Method in class com.imsl.stat.StepwiseRegression: Returns an array containing information indicating whether or not a particular variable is in the model.
getTStatistic(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests: Returns the t-statistic for the test that the i-th coefficient is zero.
getTStatistic(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests: Returns the student-t test statistic for testing the i-th coefficient equal to zero ( ${beta}_{index} = 0$ ).
getTTest() - Method in class com.imsl.stat.NormOneSample: Returns the test statistic associated with the t test.
getTTest() - Method in class com.imsl.stat.NormTwoSample: Returns the test statistic for the Satterthwaite's approximation.
getTTestDF() - Method in class com.imsl.stat.NormOneSample: Returns the degrees of freedom associated with the t test for the mean.
getTTestDF() - Method in class com.imsl.stat.NormTwoSample: Returns the degrees of freedom for the Satterthwaite's approximation for t-test for either equal or unequal variances, depending on the value set by setUnequalVariances.
getTTestP() - Method in class com.imsl.stat.NormOneSample: Returns the probability associated with the t test of a larger t in absolute value.
getTTestP() - Method in class com.imsl.stat.NormTwoSample: Returns the approximate probability of a larger t for the Satterthwaite's approximation for equal or unequal variances.
getTable() - Method in class com.imsl.stat.TableMultiWay.BalancedTable: Returns an array containing the frequencies for each variable.
getTable() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable: Returns the frequency for each cell.
getTerminationCriterion() - Method in class com.imsl.math.MinConNLP: Returns the reason the solve step terminated.
getTestEffects() - Method in class com.imsl.stat.ANOVAFactorial: Returns statistics relating to the sums of squares for the effects in the model.
getTextAngle() - Method in class com.imsl.chart.ChartNode: Returns the value of the "TextAngle" attribute.
getTextColor() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "TextColor" attribute.
getTextColor() - Method in class com.imsl.chart.ChartNode: Returns the value of the "TextColor" attribute.
getTextFormat() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "TextFormat" attribute.
getTickInterval() - Method in class com.imsl.chart.Axis1D: Retrieves the tick interval.
getTickInterval() - Method in class com.imsl.chart.AxisR: Retrieves the tick interval.
getTickInterval() - Method in class com.imsl.chart3d.Axis3D: Retrieves the tick interval.
getTickLength() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "TickLength" attribute.
getTicks() - Method in class com.imsl.chart.Axis1D: Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart.AxisR: Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart.AxisTheta: Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart3d.Axis3D: Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart3d.ColormapLegend: Returns the value of the "Ticks" attribute, if set.
getTime(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTime(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTime(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTime(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTimes() - Static method in class com.imsl.stat.KaplanMeierECDF: Retrieves the time values where the step function CDF jumps to a greater value.
getTimestamp(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.
getTimestamp(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object.
getTimestamp(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.
getTimestamp(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.
getTitle() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Title" attribute.
getTitle() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "Title" attribute.
getTo() - Method in class com.imsl.datamining.neural.Link: Returns the destination Node for this Link.
getTolerance() - Method in class com.imsl.chart.DrawMap: Get the minimum distance that an event can be from a point or a line and still be considered a hit.
getTolerance() - Method in class com.imsl.chart.DrawPick: Get the minimum distance that an event can be from a point or a line and still be considered a hit.
getTolerance() - Method in class com.imsl.math.MinConNLP: Returns the desired precision of the solution.
getToolTip() - Method in class com.imsl.chart.ChartNode: Returns the value of the "ToolTip" attribute.
getTotalDegreesOfFreedom() - Method in class com.imsl.stat.ANOVA: Returns the total degrees of freedom.
getTotalMissing() - Method in class com.imsl.stat.ANOVA: Returns the total number of missing values.
getTotalMissing() - Method in class com.imsl.stat.EmpiricalQuantiles: Returns the total number of missing values.
getTotalSumOfSquares() - Method in class com.imsl.stat.ANOVA: Returns the total sum of squares.
getTrainingIterations() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the number of iterations used during training.
getTransform() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Transform" attribute.
getTransform() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Retrieves the transform flag used for encoding and decoding.
getTukeyScores(double[]) - Method in class com.imsl.stat.Ranks: Gets the Tukey version of normal scores for each observation.
getType() - Method in class com.imsl.chart.Axis1D: Returns the axis type.
getType() - Method in class com.imsl.chart.Grid: Returns the axis type.
getType() - Method in class com.imsl.chart3d.Axis3D: Returns the axis type.
getType() - Method in class com.imsl.io.AbstractFlatFile: Returns the type of this ResultSet object.
getTypeVariable(int) - Method in class com.imsl.io.MPSReader: Returns the type of a variable.
getU() - Method in class com.imsl.math.SVD: Returns the left singular vectors.
getURL(String) - Method in class com.imsl.io.AbstractFlatFile: Retrieves the value of the designated column in the current row of this ResultSet object as a java.net.URL object.
getURL(int) - Method in class com.imsl.io.AbstractFlatFile: Retrieves the value of the designated column in the current row of this ResultSet object as a java.net.URL object.
getUnbalancedTable() - Method in class com.imsl.stat.TableMultiWay: Returns an object containing the unbalanced table.
getUp() - Method in class com.imsl.chart.Candlestick: Returns the CandlestickItem for up days.
getUpperAdjacentValue() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the lower adjacent value.
getUpperBound(int) - Method in class com.imsl.io.MPSReader: Returns the upper bound for a variable.
getUpperCICommonVariance() - Method in class com.imsl.stat.NormTwoSample: Returns the upper confidence limits for the common, or pooled, variance.
getUpperCIDiff() - Method in class com.imsl.stat.NormTwoSample: Returns the upper confidence limit for the mean of the first population minus the mean of the second for equal or unequal variances depending on the value set by setUnequalVariances.
getUpperCIMean() - Method in class com.imsl.stat.NormOneSample: Returns the upper confidence limit for the mean.
getUpperCIRatioVariance() - Method in class com.imsl.stat.NormTwoSample: Returns the approximate upper confidence limit for the ratio of the variance of the first population to the second.
getUpperCIVariance() - Method in class com.imsl.stat.NormOneSample: Returns the upper confidence limits for the variance.
getUpperQuartile() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the upper quartile value.
getUpperRange(int) - Method in class com.imsl.io.MPSReader: Returns the upper range value for a constraint equation.
getUseBackPropagation() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the use back propagation setting.
getV() - Method in class com.imsl.math.SVD: Returns the right singular vectors.
getValue() - Method in class com.imsl.datamining.neural.InputNode: Returns the value of this node.
getValue() - Method in class com.imsl.datamining.neural.OutputPerceptron: Returns the value of the output perceptron determined using the current network state and inputs.
getValue() - Method in class com.imsl.io.MPSReader.Element: Returns the value of the element.
getValues() - Method in class com.imsl.math.Eigen: Returns the eigenvalues of a matrix of type double.
getValues() - Method in class com.imsl.math.SymEigen: Returns the eigenvalues
getValues() - Method in class com.imsl.stat.FactorAnalysis: Returns the eigenvalues.
getValues() - Method in class com.imsl.stat.TableMultiWay.BalancedTable: Returns the values of the classification variables.
getVanDerWaerdenScores(double[]) - Method in class com.imsl.stat.Ranks: Gets the Van der Waerden version of normal scores for each observation.
getVarCovarMatrix() - Method in class com.imsl.stat.GARCH: Returns the variance-covariance matrix.
getVariance() - Method in class com.imsl.stat.ARMA: Returns the variance of the time series z.
getVariance() - Method in class com.imsl.stat.AutoCorrelation: Returns the variance of the time series x.
getVariance() - Method in class com.imsl.stat.Summary: Returns the population variance.
getVarianceX() - Method in class com.imsl.stat.CrossCorrelation: Returns the variance of time series x.
getVarianceX() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the variances of the channels of x.
getVarianceY() - Method in class com.imsl.stat.CrossCorrelation: Returns the variance of time series y.
getVarianceY() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the variances of the channels of y.
getVariances() - Method in class com.imsl.stat.FactorAnalysis: Gets the unique variances.
getVectors() - Method in class com.imsl.math.Eigen: Returns the eigenvectors.
getVectors() - Method in class com.imsl.math.SymEigen: Return the eigenvectors of a symmetric matrix of type double.
getVectors() - Method in class com.imsl.stat.FactorAnalysis: Returns the eigenvectors.
getViewPlatformTransformation(Transform3D) - Method in class com.imsl.chart3d.Chart3D: Sets the transformation for the view platform.
getViewport() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Viewport" attribute.
getViewport() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "Viewport" attribute.
getVirtualUniverse() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "Universe" attribute.
getVisibleFaces() - Method in class com.imsl.chart3d.AxisBox: Returns the flag indicating which faces of the box are to be drawn.
getWarning() - Static method in class com.imsl.Warning: Gets the WarningObject.
getWarnings() - Method in class com.imsl.io.AbstractFlatFile: Returns the first warning reported by calls on this ResultSet object.
getWeight() - Method in class com.imsl.datamining.neural.Link: Returns the weight for this Link.
getWeights() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the weights for the Links in this network.
getWeights() - Method in class com.imsl.datamining.neural.Network: Returns the weights.
getWhiskers() - Method in class com.imsl.chart.BoxPlot: Returns the Whiskers node.
getWindow() - Method in class com.imsl.chart.Axis1D: Returns the window for an Axis1D.
getWindow() - Method in class com.imsl.chart.AxisR: Returns the Window attribute.
getWindow() - Method in class com.imsl.chart.AxisTheta: Returns the window for an AxisTheta.
getWindow() - Method in class com.imsl.chart3d.Axis3D: Returns the window for an Axis1D.
getWindow() - Method in class com.imsl.chart3d.ColormapLegend: Returns the window for a ColormapLegend.
getX() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "X" attribute.
getX() - Method in class com.imsl.stat.GARCH: Returns the estimated parameter array, x.
getXHi() - Method in class com.imsl.stat.EmpiricalQuantiles: Returns the smallest element of x greater than or equal to the desired quantile.
getXLo() - Method in class com.imsl.stat.EmpiricalQuantiles: Returns the largest element of x less than or equal to the desired quantile.
getY() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Y" attribute.
getYearBasis() - Method in class com.imsl.finance.DayCountBasis: Returns the (days in year) portion of the Day Count Basis.
getZ() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "Z" attribute.
go_to(int) - Static method in class com.imsl.Dummy
gradient(double[], double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective
gradient(double[], double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
gradient(double[], double[]) - Method in interface com.imsl.math.MinConGenLin.Gradient: Public interface for the user-supplied function to compute the gradient at point x.
gradient(double[], int, double[]) - Method in interface com.imsl.math.MinConNLP.Gradient: Computes the value of the gradient of the function at the given point.
gradient(int, int, double[], boolean[], double, double[], double[], double[][]) - Method in interface com.imsl.math.MinConNonlin.Gradient: Deprecated. Computes the value of the gradient of the function at the given point.
gradient(double[], double[]) - Method in interface com.imsl.math.MinUnconMultiVar.Gradient: Public interface for the gradient of the multivariate function to be minimized.
gradient(double[]) - Method in class com.imsl.math.RadialBasis: Returns the gradient of the radial basis approximation at a point.
graphics - Variable in class com.imsl.chart.Draw

H

Heatmap - class com.imsl.chart.Heatmap.: Heatmap creates a chart from a two-dimensional array of double precision values or Color values.
Heatmap(AxisXY, double, double, double, double, Color[][]) - Constructor for class com.imsl.chart.Heatmap: Creates a Heatmap from an array of Color values.
Heatmap(AxisXY, double, double, double, double, double, double, double[][], Colormap) - Constructor for class com.imsl.chart.Heatmap: Creates a Heatmap from an array of double values and a Colormap.
Heatmap.Legend - class com.imsl.chart.Heatmap.Legend.: A legend for use with a heatmap.
HiddenLayer - class com.imsl.datamining.neural.HiddenLayer.: Hidden layer in a neural network.
HighLowClose - class com.imsl.chart.HighLowClose.: High-low-close plot of stock data.
HighLowClose(AxisXY, Date, double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose: Constructs a high-low-close chart node beginning with specified start date.
HighLowClose(AxisXY, Date, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose: Constructs a high-low-close-open chart node beginning with specified start date.
HighLowClose(AxisXY, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose: Constructs a high-low-close chart node at specified axis points.
HighLowClose(AxisXY, double[], double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose: Constructs a high-low-close-open chart node at specified axis points.
HyperRectangleQuadrature - class com.imsl.math.HyperRectangleQuadrature.: HyperRectangleQuadrature integrates a function over a hypercube.
HyperRectangleQuadrature(int) - Constructor for class com.imsl.math.HyperRectangleQuadrature: Constructs a HyperRectangleQuadrature object.
HyperRectangleQuadrature(RandomSequence) - Constructor for class com.imsl.math.HyperRectangleQuadrature: Constructs a HyperRectangleQuadrature object.
HyperRectangleQuadrature.Function - interface com.imsl.math.HyperRectangleQuadrature.Function.: Public interface function for the HyperRectangleQuadrature class.
Hyperbolic - class com.imsl.math.Hyperbolic.: Pure Java implementation of the hyperbolic functions and their inverses.
hasMoreTokens() - Method in class com.imsl.io.Tokenizer: Returns true if a call to nextToken will not generate an exception.
hashCode() - Method in class com.imsl.math.Complex: Returns a hashcode for this Complex.
haveErrorBarProperties - Variable in class com.imsl.chart.Draw
haveFillProperties - Variable in class com.imsl.chart.Draw
haveImageProperties - Variable in class com.imsl.chart.Draw
haveLineProperties - Variable in class com.imsl.chart.Draw
haveMarkerProperties - Variable in class com.imsl.chart.Draw
haveTextProperties - Variable in class com.imsl.chart.Draw
horizontalStripe(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a horizontally striped pattern.
hypergeometric(int, int, int, int) - Static method in class com.imsl.stat.Cdf: Evaluates the hypergeometric cumulative probability distribution function.
hypergeometricProb(int, int, int, int) - Static method in class com.imsl.stat.Cdf: Evaluates the hypergeometric probability density function.

I

I(double, int) - Static method in class com.imsl.math.Bessel: Evaluates a sequence of modified Bessel functions of the first kind with integer order and real argument.
I(double, double, int) - Static method in class com.imsl.math.Bessel: Evaluates a sequence of modified Bessel functions of the first kind with real order and real argument.
IEEE - class com.imsl.math.IEEE.: Pure Java implementation of the IEEE 754 functions as specified in IEEE Standard for Binary Floating-Point Arithmetic, ANSI/IEEE Standard 754-1985 (IEEE, New York).
IEEEremainder(double, double) - Static method in class com.imsl.math.JMath: Returns the IEEE remainder from x divided by p.
IMAGE - Static variable in class com.imsl.chart.Draw
IMAGE_FACTOR_ANALYSIS - Static variable in class com.imsl.stat.FactorAnalysis: Indicates image factor analysis.
IMSLException - exception com.imsl.IMSLException.: Signals that a mathematical exception has occurred.
IMSLException() - Constructor for class com.imsl.IMSLException: Constructs an IMSLException with no detail message.
IMSLException(String) - Constructor for class com.imsl.IMSLException: Constructs an IMSLException with the specified detail message.
IMSLException(String, String, Object[]) - Constructor for class com.imsl.IMSLException: Constructs an IMSLException with the specified detail message.
IMSLRuntimeException - exception com.imsl.IMSLRuntimeException.: Signals that an error has occurred.
IMSLRuntimeException() - Constructor for class com.imsl.IMSLRuntimeException: Constructs an IMSLRuntimeException with no detail message.
IMSLRuntimeException(String) - Constructor for class com.imsl.IMSLRuntimeException: Constructs an IMSLRuntimeException with the specified detail message.
IMSLRuntimeException(String, String, Object[]) - Constructor for class com.imsl.IMSLRuntimeException: Constructs an IMSLRuntimeException with the specified detail message.
INTEGER_VARIABLE - Static variable in class com.imsl.io.MPSReader: Variable must be an integer.
InputLayer - class com.imsl.datamining.neural.InputLayer.: Input layer in a neural network.
InputNode - class com.imsl.datamining.neural.InputNode.: A Node in the InputLayer.
InverseCdf - class com.imsl.stat.InverseCdf.: Inverse of user-supplied cumulative distribution function.
InverseCdf(CdfFunction) - Constructor for class com.imsl.stat.InverseCdf: Constructor for the inverse of a user-supplied cummulative distribution function.
InverseCdf.DidNotConvergeException - exception com.imsl.stat.InverseCdf.DidNotConvergeException.: The iteration did not converge
InverseCdf.DidNotConvergeException(String) - Constructor for class com.imsl.stat.InverseCdf.DidNotConvergeException
InverseCdf.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.stat.InverseCdf.DidNotConvergeException
i - Static variable in class com.imsl.math.Complex: The imaginary unit.
ilogb(double) - Static method in class com.imsl.math.IEEE: Return the binary exponent of non-zero x.
imag() - Method in class com.imsl.math.Complex: Returns the imaginary part of a Complex object.
imag(Complex) - Static method in class com.imsl.math.Complex: Returns the imaginary part of a Complex object.
image(ImageIcon) - Static method in class com.imsl.chart.FillPaint: Returns a tiling of an image.
imageObserver - Variable in class com.imsl.chart.Draw
incrementEpochCount() - Method in class com.imsl.datamining.neural.EpochTrainer: Increments the epoch counter.
infinityNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Return the infinity norm of a Complex matrix.
infinityNorm(double[][]) - Static method in class com.imsl.math.Matrix: Return the infinity norm of a matrix.
init() - Method in class com.imsl.chart.ChartServlet
insertRow() - Method in class com.imsl.io.AbstractFlatFile: Inserts the contents of the insert row into this ResultSet object and into the database.
intValue() - Method in class com.imsl.math.Complex: Returns the value of the real part as an int.
intValue() - Method in class com.imsl.math.Physical: Returns the value of this dimensionless object.
integral(double, double) - Method in class com.imsl.math.BSpline: Returns the value of an integral of the B-spline.
integral(double, double) - Method in class com.imsl.math.Spline: Returns the value of an integral of the spline.
intrate(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the interest rate of a fully invested security.
inverse() - Method in class com.imsl.math.Cholesky: Returns the inverse of this matrix
inverse() - Method in class com.imsl.math.ComplexLU: Compute the inverse of a matrix of type Complex.
inverse() - Method in class com.imsl.math.LU: Returns the inverse of the matrix used to construct this instance.
inverse() - Method in class com.imsl.math.SVD: Compute the Moore-Penrose generalized inverse of a real matrix.
inverseBeta(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the inverse of the beta cumulative probability distribution function.
inverseChi(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the inverse of the chi-squared cumulative probability distribution function.
inverseDiscreteUniform(double, int) - Static method in class com.imsl.stat.Cdf: Returns the inverse of the discrete uniform cumulative probability distribution function.
inverseExponential(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the inverse of the exponential cumulative probability distribution function.
inverseExtremeValue(double, double, double) - Static method in class com.imsl.stat.Cdf: Returns the inverse of the extreme value cumulative probability distribution function.
inverseF(double, double, double) - Static method in class com.imsl.stat.Cdf: Returns the inverse of the F cumulative probability distribution function.
inverseGamma(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the inverse of the gamma cumulative probability distribution function.
inverseGeometric(double, double) - Static method in class com.imsl.stat.Cdf: Returns the inverse of the discrete geometric cumulative probability distribution function.
inverseLogNormal(double, double, double) - Static method in class com.imsl.stat.Cdf: Returns the inverse of the standard lognormal cumulative probability distribution function.
inverseNoncentralchi(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the inverse of the noncentral chi-squared cumulative probability distribution function.
inverseNoncentralstudentsT(double, int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the inverse of the noncentral Student's t cumulative probability distribution function.
inverseNormal(double) - Static method in class com.imsl.stat.Cdf: Evaluates the inverse of the normal (Gaussian) cumulative probability distribution function.
inverseRayleigh(double, double) - Static method in class com.imsl.stat.Cdf: Returns the inverse of the Rayleigh cumulative probability distribution function.
inverseStudentsT(double, double) - Static method in class com.imsl.stat.Cdf: Returns the inverse of the Student's t cumulative probability distribution function.
inverseUniform(double, double, double) - Static method in class com.imsl.stat.Cdf: Returns the inverse of the uniform cumulative probability distribution function.
inverseWeibull(double, double, double) - Static method in class com.imsl.stat.Cdf: Returns the inverse of the Weibull cumulative probability distribution function.
ipmt(double, int, int, double, double, int) - Static method in class com.imsl.finance.Finance: Returns the interest payment for an investment for a given period.
ipvt - Variable in class com.imsl.math.ComplexLU: Pivot sequence for the factorization
ipvt - Variable in class com.imsl.math.LU: Pivot sequence for the factorization
irr(double[]) - Static method in class com.imsl.finance.Finance: Returns the internal rate of return for a schedule of cash flows.
irr(double[], double) - Static method in class com.imsl.finance.Finance: Returns the internal rate of return for a schedule of cash flows.
isAfterLast() - Method in class com.imsl.io.AbstractFlatFile: Indicates whether the cursor is after the last row in this ResultSet object.
isAncestorOf(AbstractChartNode) - Method in class com.imsl.chart.AbstractChartNode: Returns true if this node is an ancestor of the argument node.
isAttributeSet(String) - Method in class com.imsl.chart.AbstractChartNode: Determines if an attribute is defined (may have been inherited).
isAttributeSetAtThisNode(String) - Method in class com.imsl.chart.AbstractChartNode: Determines if an attribute is defined in this node (not inherited).
isBeforeFirst() - Method in class com.imsl.io.AbstractFlatFile: Indicates whether the cursor is before the first row in this ResultSet object.
isBitSet(int, int) - Static method in class com.imsl.chart.AbstractChartNode: Returns true if the bit set in flag is set in mask.
isBitSet(int, int) - Static method in class com.imsl.chart.ChartNode: Returns true if the bit set in flag is set in mask.
isFirst() - Method in class com.imsl.io.AbstractFlatFile: Indicates whether the cursor is on the first row of this ResultSet object.
isLast() - Method in class com.imsl.io.AbstractFlatFile: Indicates whether the cursor is on the last row of this ResultSet object.
isNaN(double) - Static method in class com.imsl.math.IEEE: NaN test on an argument of type double.
isNoMoreProgress() - Method in class com.imsl.math.QuadraticProgramming: Returns true if due to computer rounding error, a change in the variables fail to improve the objective function.
isProportionalWidth() - Method in class com.imsl.chart.BoxPlot: Returns the value of the attribute "ProportionalWidth".
isWeekday(GregorianCalendar) - Method in class com.imsl.chart.TransformDate: Returns true if the specified date is a weekday.
iterator() - Method in class com.imsl.io.MPSReader.Row: Returns an iterator over the elements in this row.

J

J(double, int) - Static method in class com.imsl.math.Bessel: Evaluates a sequence of Bessel functions of the first kind with integer order and real argument.
J(double, double, int) - Static method in class com.imsl.math.Bessel: Evaluate a sequence of Bessel functions of the first kind with real order and real positive argument.
JFrameChart - class com.imsl.chart.JFrameChart.: JFrameChart is a JFrame that contains a chart.
JFrameChart() - Constructor for class com.imsl.chart.JFrameChart: Creates new JFrameChart to display a chart.
JFrameChart(Chart) - Constructor for class com.imsl.chart.JFrameChart: Creates new JFrameChart to display a given chart.
JFrameChart3D - class com.imsl.chart3d.JFrameChart3D.: JFrameChart3D is a JFrame that contains a chart.
JFrameChart3D() - Constructor for class com.imsl.chart3d.JFrameChart3D: Creates new JFrameChart3D to display a chart.
JFrameChart3D(Chart3D) - Constructor for class com.imsl.chart3d.JFrameChart3D: Creates new JFrameChart3D to display a given chart.
JMath - class com.imsl.math.JMath.: Pure Java implementation of the standard java.lang.Math class.
JPanelChart - class com.imsl.chart.JPanelChart.: A Swing JPanel that contains a chart.
JPanelChart() - Constructor for class com.imsl.chart.JPanelChart: Creates new JPanelChart.
JPanelChart(Chart) - Constructor for class com.imsl.chart.JPanelChart: Creates new JPanelChart using a given Chart object.
JspBean - class com.imsl.chart.JspBean.: JspBean is used to refer to charts in a Java Server Page that are later rendered using the ChartServlet.
JspBean() - Constructor for class com.imsl.chart.JspBean: Creates a JspBean object.
jacobian(double[], double[][]) - Method in interface com.imsl.math.NonlinLeastSquares.Jacobian: Public interface for the nonlinear least squares function.
jacobian(double[], double[][]) - Method in interface com.imsl.math.ZeroSystem.Jacobian: Returns the value of the Jacobian at the given point.

K

K(double, int) - Static method in class com.imsl.math.Bessel: Evaluates a sequence of modified Bessel functions of the third kind with integer order and real argument.
K(double, double, int) - Static method in class com.imsl.math.Bessel: Evaluates a sequence of modified Bessel functions of the third kind with fractional order and real argument.
KalmanFilter - class com.imsl.stat.KalmanFilter.: Performs Kalman filtering and evaluates the likelihood function for the state-space model.
KalmanFilter(double[], double[], int, double, double) - Constructor for class com.imsl.stat.KalmanFilter: Constructor for KalmanFilter.
KaplanMeierECDF - class com.imsl.stat.KaplanMeierECDF.: Computes the Kaplan-Meier reliability function estimates or the CDF based on failure data that may be multi-censored.
KaplanMeierECDF(double[]) - Constructor for class com.imsl.stat.KaplanMeierECDF: Constructor for ARMA.
keySet() - Method in class com.imsl.chart.xml.ChartXML: Returns the Set view of all id's defined in the XML file.
knot - Variable in class com.imsl.math.BSpline: The knot array of length n + order, where n is the number of coefficients in the B-spline.
kurtosis(double[]) - Static method in class com.imsl.stat.Summary: Returns the kurtosis of the given data set.
kurtosis(double[], double[]) - Static method in class com.imsl.stat.Summary: Returns the kurtosis of the given data set and associated weights.

L

LABEL_TYPE_NONE - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate the an element is not to be labeled.
LABEL_TYPE_PERCENT - Static variable in class com.imsl.chart.ChartNode: Flag used to indicate that a pie slice is to be labeled with a percentage value.
LABEL_TYPE_TITLE - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that an element is to be labeled with the value of its title attribute.
LABEL_TYPE_X - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that an element is to be labeled with the value of its x-coordinate.
LABEL_TYPE_Y - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that an element is to be labeled with the value of its y-coordinate.
LABEL_TYPE_Z - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that an element is to be labeled with the value of its y-coordinate.
LAST - Static variable in class com.imsl.chart.Draw: Flag for the last data marker.
LEAST_SQUARES - Static variable in class com.imsl.stat.ARMA: Indicates autoregressive and moving average parameters are estimated by a least-squares procedure.
LEAVE_OUT_ONE - Static variable in class com.imsl.stat.DiscriminantAnalysis: Indicates leave-out-one as the Classicfication Method.
LENGTH - Static variable in class com.imsl.math.Physical
LINE - Static variable in class com.imsl.chart.Draw
LINEAR - Static variable in interface com.imsl.datamining.neural.Activation: The identity activation function, g(x) = x.
LINEAR - Static variable in class com.imsl.stat.DiscriminantAnalysis: Indicates a linear discrimination method.
LOGISTIC - Static variable in interface com.imsl.datamining.neural.Activation: The logistic activation function, $g(x)=frac{1}{1+e^{-x}}$ .
LOGISTIC_TABLE - Static variable in interface com.imsl.datamining.neural.Activation: The logistic activation function computed using a table.
LOWER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix: This flag as the argument to setMatrixType, indicates that only the lower triangular elements of the matrix are to be printed.
LU - class com.imsl.math.LU.: LU factorization of a matrix of type double.
LU(double[][]) - Constructor for class com.imsl.math.LU: Creates the LU factorization of a square matrix of type double.
Layer - class com.imsl.datamining.neural.Layer.: The base class for Layers in a neural network.
Layer(FeedForwardNetwork) - Constructor for class com.imsl.datamining.neural.Layer: Constructs a Layer.
LeastSquaresTrainer - class com.imsl.datamining.neural.LeastSquaresTrainer.: Trains a FeedForwardNetwork using a Levenberg-Marquardt algorithm for minimizing a sum of squares error.
LeastSquaresTrainer() - Constructor for class com.imsl.datamining.neural.LeastSquaresTrainer: Creates a LeastSquaresTrainer.
Legend - class com.imsl.chart.Legend.: The chart legend.
Legend(Chart) - Constructor for class com.imsl.chart.Legend
LicenseManagerException - exception com.imsl.LicenseManagerException.: A LicenseManagerException exception is thrown if a license to use the product cannot be obtained.
LillieforsTest() - Method in class com.imsl.stat.NormalityTest: Performs the Lilliefors test.
LinearProgramming - class com.imsl.math.LinearProgramming.: Linear programming problem using the revised simplex algorithm.
LinearProgramming(double[][], double[], double[]) - Constructor for class com.imsl.math.LinearProgramming: Constructor variables of type double.
LinearProgramming.BoundsInconsistentException - exception com.imsl.math.LinearProgramming.BoundsInconsistentException.: The bounds given are inconsistent.
LinearProgramming.BoundsInconsistentException(String) - Constructor for class com.imsl.math.LinearProgramming.BoundsInconsistentException
LinearProgramming.BoundsInconsistentException(String, Object[]) - Constructor for class com.imsl.math.LinearProgramming.BoundsInconsistentException
LinearProgramming.NumericDifficultyException - exception com.imsl.math.LinearProgramming.NumericDifficultyException.: Numerical difficulty occurred.
LinearProgramming.NumericDifficultyException(String) - Constructor for class com.imsl.math.LinearProgramming.NumericDifficultyException
LinearProgramming.NumericDifficultyException(String, Object[]) - Constructor for class com.imsl.math.LinearProgramming.NumericDifficultyException
LinearProgramming.ProblemInfeasibleException - exception com.imsl.math.LinearProgramming.ProblemInfeasibleException.: The problem is not feasible.
LinearProgramming.ProblemInfeasibleException(String) - Constructor for class com.imsl.math.LinearProgramming.ProblemInfeasibleException
LinearProgramming.ProblemInfeasibleException() - Constructor for class com.imsl.math.LinearProgramming.ProblemInfeasibleException
LinearProgramming.ProblemUnboundedException - exception com.imsl.math.LinearProgramming.ProblemUnboundedException.: The problem is unbounded.
LinearProgramming.ProblemUnboundedException(String) - Constructor for class com.imsl.math.LinearProgramming.ProblemUnboundedException
LinearProgramming.ProblemUnboundedException() - Constructor for class com.imsl.math.LinearProgramming.ProblemUnboundedException
LinearRegression - class com.imsl.stat.LinearRegression.: Fits a multiple linear regression model with or without an intercept.
LinearRegression(int, boolean) - Constructor for class com.imsl.stat.LinearRegression: Constructs a new linear regression object.
LinearRegression.CaseStatistics - class com.imsl.stat.LinearRegression.CaseStatistics.: Inner Class CaseStatistics allows for the computation of predicted values, confidence intervals, and diagnostics for detecting outliers and cases that greatly influence the fitted regression.
LinearRegression.CoefficientTTests - class com.imsl.stat.LinearRegression.CoefficientTTests.: Contains statistics related to the regression coefficients.
Link - class com.imsl.datamining.neural.Link.: A link in a neural network.
label(int) - Static method in class com.imsl.Dummy
last() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the last row in this ResultSet object.
lineColor - Variable in class com.imsl.chart.Draw
lineDashPattern - Variable in class com.imsl.chart.Draw
lineWidth - Variable in class com.imsl.chart.Draw
link(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Establishes a Link between two Nodes.
link(Node, Node, double) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Establishes a Link between two Nodes with a specified weight.
linkAll(Layer, Layer) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Link all of the Nodes in one Layer to all of the Nodes in another Layer.
linkAll() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: For each Layer in the Network, link each Node in the Layer to each Node in the next Layer.
log(Complex) - Static method in class com.imsl.math.Complex: Returns the logarithm of a Complex z, with a branch cut along the negative real axis.
log(double) - Static method in class com.imsl.math.JMath: Returns the natural logarithm of a double.
log10(double) - Static method in class com.imsl.math.Sfun: Returns the common (base 10) logarithm of a double.
log1p(double) - Static method in class com.imsl.math.Hyperbolic: Returns log(1+x), the logarithm of (x plus 1).
logBeta(double, double) - Static method in class com.imsl.math.Sfun: Returns the logarithm of the Beta function.
logGamma(double) - Static method in class com.imsl.math.Sfun: Returns the logarithm of the Gamma function of the absolute value of a double.
logNormal(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the standard lognormal cumulative probability distribution function.
logNormalProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the standard lognormal probability density function.
longValue() - Method in class com.imsl.math.Complex: Returns the value of the real part as a long.
longValue() - Method in class com.imsl.math.Physical: Returns the value of this dimensionless object.

M

MALLOWS_CP_CRITERION - Static variable in class com.imsl.stat.SelectionRegression: Indicates Mallow's criterion regression.
MARKER - Static variable in class com.imsl.chart.Draw
MARKER_SCALE - Static variable in class com.imsl.chart.Draw: Normal marker size in pixels is screen width times MARKER_SCALE.
MARKER_TYPE_ASTERISK - Static variable in class com.imsl.chart.ChartNode: Flag for a asterisk data marker.
MARKER_TYPE_CIRCLE_CIRCLE - Static variable in class com.imsl.chart.ChartNode: Flag for a circle in a circle data marker.
MARKER_TYPE_CIRCLE_PLUS - Static variable in class com.imsl.chart.ChartNode: Flag for a plus in a circle data marker.
MARKER_TYPE_CIRCLE_X - Static variable in class com.imsl.chart.ChartNode: Flag for an x in a circle data marker.
MARKER_TYPE_CUBE - Static variable in class com.imsl.chart3d.ChartNode3D: Flag for a cube data marker.
MARKER_TYPE_CUSTOM - Static variable in class com.imsl.chart3d.ChartNode3D: Flag for a custom marker
MARKER_TYPE_DIAMOND_PLUS - Static variable in class com.imsl.chart.ChartNode: Flag for a plus in a diamond data marker.
MARKER_TYPE_FILLED_CIRCLE - Static variable in class com.imsl.chart.ChartNode: Flag for a filled circle data marker.
MARKER_TYPE_FILLED_DIAMOND - Static variable in class com.imsl.chart.ChartNode: Flag for a filled diamond data marker.
MARKER_TYPE_FILLED_SQUARE - Static variable in class com.imsl.chart.ChartNode: Flag for a filled square data marker.
MARKER_TYPE_FILLED_TRIANGLE - Static variable in class com.imsl.chart.ChartNode: Flag for a filled triangle data marker.
MARKER_TYPE_HOLLOW_CIRCLE - Static variable in class com.imsl.chart.ChartNode: Flag for a hollow circle data marker.
MARKER_TYPE_HOLLOW_DIAMOND - Static variable in class com.imsl.chart.ChartNode: Flag for a hollow diamond data marker.
MARKER_TYPE_HOLLOW_SQUARE - Static variable in class com.imsl.chart.ChartNode: Flag for a hollow square data marker.
MARKER_TYPE_HOLLOW_TRIANGLE - Static variable in class com.imsl.chart.ChartNode: Flag for hollow triangle data marker.
MARKER_TYPE_OCTAGON_PLUS - Static variable in class com.imsl.chart.ChartNode: Flag for a plus in an octagon data marker.
MARKER_TYPE_OCTAGON_X - Static variable in class com.imsl.chart.ChartNode: Flag for a x in an octagon data marker.
MARKER_TYPE_PLUS - Static variable in class com.imsl.chart.ChartNode: Flag for a plus-shaped data marker.
MARKER_TYPE_PLUS - Static variable in class com.imsl.chart3d.ChartNode3D: Flag for a 3D plus sign data marker.
MARKER_TYPE_SIMPLE_CUBE - Static variable in class com.imsl.chart3d.ChartNode3D: Flag for a simple cube (no edge) data marker.
MARKER_TYPE_SIMPLE_PLUS - Static variable in class com.imsl.chart3d.ChartNode3D: Flag for a simple 2D plus sign (no edge) data marker.
MARKER_TYPE_SIMPLE_TETRAHEDRON - Static variable in class com.imsl.chart3d.ChartNode3D: Flag for a simple tetrahedron (no edge) data marker.
MARKER_TYPE_SPHERE - Static variable in class com.imsl.chart3d.ChartNode3D: Flag for a sphere data marker.
MARKER_TYPE_SQUARE_PLUS - Static variable in class com.imsl.chart.ChartNode: Flag for a plus in a square data marker.
MARKER_TYPE_SQUARE_X - Static variable in class com.imsl.chart.ChartNode: Flag for an x in a square data marker.
MARKER_TYPE_TETRAHEDRON - Static variable in class com.imsl.chart3d.ChartNode3D: Flag for a tetrahedron data marker.
MARKER_TYPE_X - Static variable in class com.imsl.chart.ChartNode: Flag for a x-shaped data marker.
MASS - Static variable in class com.imsl.math.Physical
MAXIMUM_LIKELIHOOD - Static variable in class com.imsl.stat.FactorAnalysis: Indicates maximum likelihood method.
METHOD_OF_MOMENTS - Static variable in class com.imsl.stat.ARMA: Indicates autoregressive and moving average parameters are estimated by a method of moments procedure.
MODEL0 - Static variable in class com.imsl.stat.CategoricalGenLinModel: Indicates an exponential function is used to model the distribution parameter.
MODEL1 - Static variable in class com.imsl.stat.CategoricalGenLinModel: Indicates a logistic function is used to model the distribution parameter.
MODEL2 - Static variable in class com.imsl.stat.CategoricalGenLinModel: Indicates a logistic function is used to model the distribution parameter.
MODEL3 - Static variable in class com.imsl.stat.CategoricalGenLinModel: Indicates a logistic function is used to model the distribution parameter.
MODEL4 - Static variable in class com.imsl.stat.CategoricalGenLinModel: Indicates a probit function is used to model the distribution parameter.
MODEL5 - Static variable in class com.imsl.stat.CategoricalGenLinModel: Indicates a log-log function is used to model the distribution parameter.
MORANS_FORMULA - Static variable in class com.imsl.stat.AutoCorrelation: Indicates standard error computation using Moran's formula.
MPSReader - class com.imsl.io.MPSReader.: Reads a linear programming problem from an MPS file.
MPSReader() - Constructor for class com.imsl.io.MPSReader
MPSReader.Element - class com.imsl.io.MPSReader.Element.: An element in the sparse contraint matrix.
MPSReader.InvalidMPSFileException - exception com.imsl.io.MPSReader.InvalidMPSFileException.: The MPS file is invalid.
MPSReader.InvalidMPSFileException(String) - Constructor for class com.imsl.io.MPSReader.InvalidMPSFileException
MPSReader.InvalidMPSFileException(String, Object[]) - Constructor for class com.imsl.io.MPSReader.InvalidMPSFileException
MPSReader.Row - class com.imsl.io.MPSReader.Row.: A row either in the constraint matrix or a free row.
MajorTick - class com.imsl.chart.MajorTick.: The major tick marks.
MajorTick - class com.imsl.chart3d.MajorTick.: Major ticks marks.
Matrix - class com.imsl.math.Matrix.: Matrix manipulation functions.
MersenneTwister - class com.imsl.stat.MersenneTwister.: A 32-bit Mersenne Twister generator.
MersenneTwister(int) - Constructor for class com.imsl.stat.MersenneTwister: Constructor for the MersenneTwister class with supplied seed.
MersenneTwister(int[]) - Constructor for class com.imsl.stat.MersenneTwister: Constructor for the MersenneTwister class with supplied array.
MersenneTwister64 - class com.imsl.stat.MersenneTwister64.: A 64-bit Mersenne Twister generator.
MersenneTwister64(long) - Constructor for class com.imsl.stat.MersenneTwister64: Constructor for the MersenneTwister64 class with supplied seed.
MersenneTwister64(long[]) - Constructor for class com.imsl.stat.MersenneTwister64: Constructor for the MersenneTwister64 class with supplied array.
Messages - class com.imsl.Messages.: Retrieve and format message strings.
Messages() - Constructor for class com.imsl.Messages
MinConGenLin - class com.imsl.math.MinConGenLin.: Minimizes a general objective function subject to linear equality/inequality constraints.
MinConGenLin(MinConGenLin.Function, int, int, int, double[], double[], double[], double[]) - Constructor for class com.imsl.math.MinConGenLin: Constructor for MinConGenLin.
MinConGenLin.ConstraintsInconsistentException - exception com.imsl.math.MinConGenLin.ConstraintsInconsistentException.: The equality constraints are inconsistent.
MinConGenLin.ConstraintsInconsistentException(String) - Constructor for class com.imsl.math.MinConGenLin.ConstraintsInconsistentException
MinConGenLin.ConstraintsInconsistentException(String, Object[]) - Constructor for class com.imsl.math.MinConGenLin.ConstraintsInconsistentException
MinConGenLin.ConstraintsNotSatisfiedException - exception com.imsl.math.MinConGenLin.ConstraintsNotSatisfiedException.: No vector x satisfies all of the constraints.
MinConGenLin.ConstraintsNotSatisfiedException(String) - Constructor for class com.imsl.math.MinConGenLin.ConstraintsNotSatisfiedException
MinConGenLin.ConstraintsNotSatisfiedException(String, Object[]) - Constructor for class com.imsl.math.MinConGenLin.ConstraintsNotSatisfiedException
MinConGenLin.EqualityConstraintsException - exception com.imsl.math.MinConGenLin.EqualityConstraintsException.: the variables are determined by the equality constraints.
MinConGenLin.EqualityConstraintsException(String) - Constructor for class com.imsl.math.MinConGenLin.EqualityConstraintsException
MinConGenLin.EqualityConstraintsException(String, Object[]) - Constructor for class com.imsl.math.MinConGenLin.EqualityConstraintsException
MinConGenLin.Function - interface com.imsl.math.MinConGenLin.Function.: Public interface for the user-supplied function to evaluate the function to be minimized.
MinConGenLin.Gradient - interface com.imsl.math.MinConGenLin.Gradient.: Public interface for the user-supplied function to compute the gradient.
MinConGenLin.VarBoundsInconsistentException - exception com.imsl.math.MinConGenLin.VarBoundsInconsistentException.: The equality constraints and the bounds on the variables are found to be inconsistent.
MinConGenLin.VarBoundsInconsistentException(String) - Constructor for class com.imsl.math.MinConGenLin.VarBoundsInconsistentException
MinConGenLin.VarBoundsInconsistentException(String, Object[]) - Constructor for class com.imsl.math.MinConGenLin.VarBoundsInconsistentException
MinConNLP - class com.imsl.math.MinConNLP.: General nonlinear programming solver.
MinConNLP(int, int, int) - Constructor for class com.imsl.math.MinConNLP: Nonlinear programming solver constructor.
MinConNLP.BadInitialGuessException - exception com.imsl.math.MinConNLP.BadInitialGuessException.: Penalty function point infeasible for original problem.
MinConNLP.BadInitialGuessException(String) - Constructor for class com.imsl.math.MinConNLP.BadInitialGuessException
MinConNLP.BadInitialGuessException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.BadInitialGuessException
MinConNLP.ConstraintEvaluationException - exception com.imsl.math.MinConNLP.ConstraintEvaluationException.: Constraint evaluation returns an error with current point.
MinConNLP.ConstraintEvaluationException(String) - Constructor for class com.imsl.math.MinConNLP.ConstraintEvaluationException
MinConNLP.ConstraintEvaluationException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.ConstraintEvaluationException
MinConNLP.Formatter - class com.imsl.math.MinConNLP.Formatter.: Simple formatter for MinConNLP logging
MinConNLP.Formatter() - Constructor for class com.imsl.math.MinConNLP.Formatter
MinConNLP.Function - interface com.imsl.math.MinConNLP.Function.: Public interface for the user supplied function to the MinConNLP object.
MinConNLP.Gradient - interface com.imsl.math.MinConNLP.Gradient.: Public interface for the user supplied function to compute the gradient for MinConNLP object.
MinConNLP.IllConditionedException - exception com.imsl.math.MinConNLP.IllConditionedException.: Problem is singular or ill-conditioned.
MinConNLP.IllConditionedException(String) - Constructor for class com.imsl.math.MinConNLP.IllConditionedException
MinConNLP.IllConditionedException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.IllConditionedException
MinConNLP.LimitingAccuracyException - exception com.imsl.math.MinConNLP.LimitingAccuracyException.: Limiting accuracy reached for a singular problem.
MinConNLP.LimitingAccuracyException(String) - Constructor for class com.imsl.math.MinConNLP.LimitingAccuracyException
MinConNLP.LimitingAccuracyException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.LimitingAccuracyException
MinConNLP.LinearlyDependentGradientsException - exception com.imsl.math.MinConNLP.LinearlyDependentGradientsException.: Working set gradients are linearly dependent.
MinConNLP.LinearlyDependentGradientsException(String) - Constructor for class com.imsl.math.MinConNLP.LinearlyDependentGradientsException
MinConNLP.LinearlyDependentGradientsException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.LinearlyDependentGradientsException
MinConNLP.NoAcceptableStepsizeException - exception com.imsl.math.MinConNLP.NoAcceptableStepsizeException.: No acceptable stepsize in [SIGMA,SIGLA].
MinConNLP.NoAcceptableStepsizeException(String) - Constructor for class com.imsl.math.MinConNLP.NoAcceptableStepsizeException
MinConNLP.NoAcceptableStepsizeException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.NoAcceptableStepsizeException
MinConNLP.ObjectiveEvaluationException - exception com.imsl.math.MinConNLP.ObjectiveEvaluationException.: Objective evaluation returns an error with current point.
MinConNLP.ObjectiveEvaluationException(String) - Constructor for class com.imsl.math.MinConNLP.ObjectiveEvaluationException
MinConNLP.ObjectiveEvaluationException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.ObjectiveEvaluationException
MinConNLP.PenaltyFunctionPointInfeasibleException - exception com.imsl.math.MinConNLP.PenaltyFunctionPointInfeasibleException.: Penalty function point infeasible.
MinConNLP.PenaltyFunctionPointInfeasibleException(String) - Constructor for class com.imsl.math.MinConNLP.PenaltyFunctionPointInfeasibleException
MinConNLP.PenaltyFunctionPointInfeasibleException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.PenaltyFunctionPointInfeasibleException
MinConNLP.QPInfeasibleException - exception com.imsl.math.MinConNLP.QPInfeasibleException.: QP problem seemingly infeasible.
MinConNLP.QPInfeasibleException(String) - Constructor for class com.imsl.math.MinConNLP.QPInfeasibleException
MinConNLP.QPInfeasibleException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.QPInfeasibleException
MinConNLP.SingularException - exception com.imsl.math.MinConNLP.SingularException.: Problem is singular.
MinConNLP.SingularException(String) - Constructor for class com.imsl.math.MinConNLP.SingularException
MinConNLP.SingularException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.SingularException
MinConNLP.TerminationCriteriaNotSatisfiedException - exception com.imsl.math.MinConNLP.TerminationCriteriaNotSatisfiedException.: Termination criteria are not satisfied.
MinConNLP.TerminationCriteriaNotSatisfiedException(String) - Constructor for class com.imsl.math.MinConNLP.TerminationCriteriaNotSatisfiedException
MinConNLP.TerminationCriteriaNotSatisfiedException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.TerminationCriteriaNotSatisfiedException
MinConNLP.TooManyIterationsException - exception com.imsl.math.MinConNLP.TooManyIterationsException.: Maximum number of iterations exceeded.
MinConNLP.TooManyIterationsException(String) - Constructor for class com.imsl.math.MinConNLP.TooManyIterationsException
MinConNLP.TooManyIterationsException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.TooManyIterationsException
MinConNLP.TooMuchTimeException - exception com.imsl.math.MinConNLP.TooMuchTimeException.: Maximum time allowed for solve exceeded.
MinConNLP.TooMuchTimeException(long) - Constructor for class com.imsl.math.MinConNLP.TooMuchTimeException
MinConNLP.WorkingSetSingularException - exception com.imsl.math.MinConNLP.WorkingSetSingularException.: Working set is singular in dual extended QP.
MinConNLP.WorkingSetSingularException(String) - Constructor for class com.imsl.math.MinConNLP.WorkingSetSingularException
MinConNLP.WorkingSetSingularException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.WorkingSetSingularException
MinConNonlin.Function - interface com.imsl.math.MinConNonlin.Function.: Deprecated. Public interface for the user supplied function to the MinConNonlin object.
MinConNonlin.Gradient - interface com.imsl.math.MinConNonlin.Gradient.: Deprecated. Public interface for the user supplied function to MinConNonlin object.
MinConNonlin.LineSearchException - exception com.imsl.math.MinConNonlin.LineSearchException.: Deprecated. The line search used more than 5 function calls, therefore it has been declared unsuccessful.
MinConNonlin.LineSearchException(String) - Constructor for class com.imsl.math.MinConNonlin.LineSearchException: Deprecated.
MinConNonlin.LineSearchException(String, Object[]) - Constructor for class com.imsl.math.MinConNonlin.LineSearchException: Deprecated.
MinConNonlin.QPConstraintsException - exception com.imsl.math.MinConNonlin.QPConstraintsException.: Deprecated. The constraints for the QP subproblem are inconsistent.
MinConNonlin.QPConstraintsException(String) - Constructor for class com.imsl.math.MinConNonlin.QPConstraintsException: Deprecated.
MinConNonlin.QPConstraintsException(String, Object[]) - Constructor for class com.imsl.math.MinConNonlin.QPConstraintsException: Deprecated.
MinConNonlin.TooManyIterationsException - exception com.imsl.math.MinConNonlin.TooManyIterationsException.: Deprecated. Maximum number of iterations exceeded.
MinConNonlin.TooManyIterationsException(String) - Constructor for class com.imsl.math.MinConNonlin.TooManyIterationsException: Deprecated.
MinConNonlin.TooManyIterationsException(String, Object[]) - Constructor for class com.imsl.math.MinConNonlin.TooManyIterationsException: Deprecated.
MinConNonlin.UphillSearchCalcException - exception com.imsl.math.MinConNonlin.UphillSearchCalcException.: Deprecated. The algorithm calculated an uphill search direction.
MinConNonlin.UphillSearchCalcException(String) - Constructor for class com.imsl.math.MinConNonlin.UphillSearchCalcException: Deprecated.
MinConNonlin.UphillSearchCalcException(String, Object[]) - Constructor for class com.imsl.math.MinConNonlin.UphillSearchCalcException: Deprecated.
MinConNonlin.ZeroSearchDirectionException - exception com.imsl.math.MinConNonlin.ZeroSearchDirectionException.: Deprecated. The search direction is close to zero.
MinConNonlin.ZeroSearchDirectionException(String) - Constructor for class com.imsl.math.MinConNonlin.ZeroSearchDirectionException: Deprecated.
MinConNonlin.ZeroSearchDirectionException(String, Object[]) - Constructor for class com.imsl.math.MinConNonlin.ZeroSearchDirectionException: Deprecated.
MinUncon - class com.imsl.math.MinUncon.: Unconstrained minimization.
MinUncon() - Constructor for class com.imsl.math.MinUncon: Unconstrained minimum constructor for a smooth function of a single variable of type double.
MinUncon.Derivative - interface com.imsl.math.MinUncon.Derivative.: Public interface for the user supplied function to the MinUncon object.
MinUncon.Function - interface com.imsl.math.MinUncon.Function.: Public interface for the user supplied function to the MinUncon object.
MinUnconMultiVar - class com.imsl.math.MinUnconMultiVar.: Unconstrained multivariate minimization.
MinUnconMultiVar(int) - Constructor for class com.imsl.math.MinUnconMultiVar: Unconstrained minimum constructor for a function of n variables of type double.
MinUnconMultiVar.ApproximateMinimumException - exception com.imsl.math.MinUnconMultiVar.ApproximateMinimumException.: Scaled step tolerance satisfied; the current point may be an approximate local solution, or the algorithm is making very slow progress and is not near a solution, or the scaled step tolerance is too big.
MinUnconMultiVar.ApproximateMinimumException(String) - Constructor for class com.imsl.math.MinUnconMultiVar.ApproximateMinimumException
MinUnconMultiVar.ApproximateMinimumException(String, Object[]) - Constructor for class com.imsl.math.MinUnconMultiVar.ApproximateMinimumException
MinUnconMultiVar.FalseConvergenceException - exception com.imsl.math.MinUnconMultiVar.FalseConvergenceException.: False convergence error; the iterates appear to be converging to a noncritical point.
MinUnconMultiVar.FalseConvergenceException(String) - Constructor for class com.imsl.math.MinUnconMultiVar.FalseConvergenceException
MinUnconMultiVar.FalseConvergenceException(String, Object[]) - Constructor for class com.imsl.math.MinUnconMultiVar.FalseConvergenceException
MinUnconMultiVar.Function - interface com.imsl.math.MinUnconMultiVar.Function.: Public interface for the user supplied function to the MinUnconMultiVar object.
MinUnconMultiVar.Gradient - interface com.imsl.math.MinUnconMultiVar.Gradient.: Public interface for the user supplied gradient to the MinUnconMultiVar object.
MinUnconMultiVar.MaxIterationsException - exception com.imsl.math.MinUnconMultiVar.MaxIterationsException.: Maximum number of iterations exceeded.
MinUnconMultiVar.MaxIterationsException(String) - Constructor for class com.imsl.math.MinUnconMultiVar.MaxIterationsException
MinUnconMultiVar.MaxIterationsException(String, Object[]) - Constructor for class com.imsl.math.MinUnconMultiVar.MaxIterationsException
MinUnconMultiVar.UnboundedBelowException - exception com.imsl.math.MinUnconMultiVar.UnboundedBelowException.: Five consecutive steps of the maximum allowable stepsize have been taken, either the function is unbounded below, or has a finite asymptote in some direction or the maximum allowable step size is too small.
MinUnconMultiVar.UnboundedBelowException(String) - Constructor for class com.imsl.math.MinUnconMultiVar.UnboundedBelowException
MinUnconMultiVar.UnboundedBelowException(String, Object[]) - Constructor for class com.imsl.math.MinUnconMultiVar.UnboundedBelowException
MinorTick - class com.imsl.chart.MinorTick.: The minor tick marks.
MultiClassification - class com.imsl.datamining.neural.MultiClassification.: Classifies patterns into three or more classes.
MultiClassification(Network) - Constructor for class com.imsl.datamining.neural.MultiClassification: Creates a classifier.
MultiCrossCorrelation - class com.imsl.stat.MultiCrossCorrelation.: Computes the multichannel cross-correlation function of two mutually stationary multichannel time series.
MultiCrossCorrelation(double[][], double[][], int) - Constructor for class com.imsl.stat.MultiCrossCorrelation: Constructor to compute the multichannel cross-correlation function of two mutually stationary multichannel time series.
MultiCrossCorrelation.NonPosVariancesException - exception com.imsl.stat.MultiCrossCorrelation.NonPosVariancesException.: The problem is ill-conditioned.
MultiCrossCorrelation.NonPosVariancesException(String) - Constructor for class com.imsl.stat.MultiCrossCorrelation.NonPosVariancesException
MultiCrossCorrelation.NonPosVariancesException(String, Object[]) - Constructor for class com.imsl.stat.MultiCrossCorrelation.NonPosVariancesException
MultipleComparisons - class com.imsl.stat.MultipleComparisons.: Performs Student-Newman-Keuls multiple comparisons test.
MultipleComparisons(double[], int, double) - Constructor for class com.imsl.stat.MultipleComparisons: Constructor for MultipleComparisons.
main(String[]) - Static method in class com.imsl.Version: Print the version information about the envirnoment and this library.
main(String[]) - Static method in class com.imsl.chart.xml.ChartXML: Displays a chart created from an XML file.
mapCubeToUser(double, double, double, double[]) - Method in class com.imsl.chart3d.AxisXYZ: Map the cube coordinates to user coordinates.
mapDeviceToUser(int, int, double[]) - Method in class com.imsl.chart.Axis: Maps the device coordinates to user coordinates.
mapDeviceToUser(int, int, double[]) - Method in class com.imsl.chart.AxisXY: Map the device coordinates to user coordinates.
mapDeviceToUser(int, int, double[]) - Method in class com.imsl.chart.Pie: Maps the device coordinates to user coordinates.
mapDeviceToUser(int, int, double[]) - Method in class com.imsl.chart.Polar: Map the device coordinates to polar coordinates.
mapUnitToUser(double) - Method in interface com.imsl.chart.Transform: Maps points in the interval [0,1] to user coordinates.
mapUnitToUser(double) - Method in class com.imsl.chart.TransformDate: Maps points in the interval [0,1] to user coordinates.
mapUserToCube(double, double, double, double[]) - Method in class com.imsl.chart3d.AxisXYZ: Map the user coordinates (userX,userY) to the cube coordinates cubeXYZ.
mapUserToDevice(double, double, int[]) - Method in class com.imsl.chart.Axis: Maps the user coordinates (userX,userY) to the device coordinates devXY.
mapUserToDevice(double, double, int[]) - Method in class com.imsl.chart.AxisXY: Map the user coordinates (userX,userY) to the device coordinates devXY.
mapUserToDevice(double, double, int[]) - Method in class com.imsl.chart.Pie: Maps the user coordinates (userX,userY) to the device coordinates devXY.
mapUserToDevice(double, double, int[]) - Method in class com.imsl.chart.Polar: Map the polar coordinates (userRadius,userAngle) to the device coordinates devXY.
mapUserToUnit(double) - Method in interface com.imsl.chart.Transform: Maps user coordinate to the interval [0,1].
mapUserToUnit(double) - Method in class com.imsl.chart.TransformDate: Maps user coordinate to the interval [0,1].
markerColor - Variable in class com.imsl.chart.Draw
markerDashPattern - Variable in class com.imsl.chart.Draw
markerSize - Variable in class com.imsl.chart.Draw
markerThickness - Variable in class com.imsl.chart.Draw
markerType - Variable in class com.imsl.chart.Draw
max(int, int) - Static method in class com.imsl.math.JMath: Returns the larger of two ints.
max(long, long) - Static method in class com.imsl.math.JMath: Returns the larger of two longs.
max(float, float) - Static method in class com.imsl.math.JMath: Returns the larger of two floats.
max(double, double) - Static method in class com.imsl.math.JMath: Returns the larger of two doubles.
maximum(double[]) - Static method in class com.imsl.stat.Summary: Returns the maximum of the given data set.
mduration(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the modified Macauley duration for a security with an assumed par value of $100.
mean(double[]) - Static method in class com.imsl.stat.Summary: Returns the mean of the given data set.
mean(double[], double[]) - Static method in class com.imsl.stat.Summary: Returns the mean of the given data set with associated weights.
median(double[]) - Static method in class com.imsl.stat.Summary: Returns the median of the given data set.
min(int, int) - Static method in class com.imsl.math.JMath: Returns the smaller of two ints.
min(long, long) - Static method in class com.imsl.math.JMath: Returns the smaller of two longs.
min(float, float) - Static method in class com.imsl.math.JMath: Returns the smaller of two floats.
min(double, double) - Static method in class com.imsl.math.JMath: Returns the smaller of two doubles.
minimum(double[]) - Static method in class com.imsl.stat.Summary: Returns the minimum of the given data set.
mirr(double[], double, double) - Static method in class com.imsl.finance.Finance: Returns the modified internal rate of return for a schedule of periodic cash flows.
mode(double[]) - Static method in class com.imsl.stat.Summary: Returns the mode of the given data set.
mouseDragged(MouseEvent) - Method in class com.imsl.chart.ToolTip: Part of the MouseMotionListener interface.
mouseMoved(MouseEvent) - Method in class com.imsl.chart.ToolTip: Part of the MouseMotionListener interface.
moveToCurrentRow() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the remembered cursor position, usually the current row.
moveToInsertRow() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the insert row.
multiply(Complex, Complex) - Static method in class com.imsl.math.Complex: Returns the product of two Complex objects, x * y.
multiply(Complex, double) - Static method in class com.imsl.math.Complex: Returns the product of a Complex object and a double, x * y.
multiply(double, Complex) - Static method in class com.imsl.math.Complex: Returns the product of a double and a Complex object, x * y.
multiply(Complex[], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Return the product of the row vector x and the rectangular array a, both Complex.
multiply(Complex[][], Complex[]) - Static method in class com.imsl.math.ComplexMatrix: Multiply the rectangular array a and the column vector x, both Complex.
multiply(Complex[][], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Multiply two Complex rectangular arrays, a * b.
multiply(double[], double[][]) - Static method in class com.imsl.math.Matrix: Return the product of the row array x and the rectangular array a.
multiply(double[][], double[]) - Static method in class com.imsl.math.Matrix: Multiply the rectangular array a and the column array x.
multiply(double[][], double[][]) - Static method in class com.imsl.math.Matrix: Multiply two rectangular arrays, a * b.
multiply(Physical, Physical) - Static method in class com.imsl.math.Physical: Multiply two Physical objects.
multiply(Physical, double) - Static method in class com.imsl.math.Physical: Multiply a Physical object and a double
multiply(double, Physical) - Static method in class com.imsl.math.Physical: Multiply a double and a Physical object
multiplyImag(Complex, double) - Static method in class com.imsl.math.Complex: Returns the product of a Complex object and a pure imaginary double, x * iy.
multiplyImag(double, Complex) - Static method in class com.imsl.math.Complex: Returns the product of a pure imaginary double and a Complex object, ix * y.

N

NONE - Static variable in class com.imsl.chart.Draw
NOT_A_KNOT - Static variable in class com.imsl.math.CsInterpolate
NO_SCALING - Static variable in class com.imsl.datamining.neural.ScaleFilter: Flag to indicate no scaling.
Network - class com.imsl.datamining.neural.Network.: Neural network base class.
Network() - Constructor for class com.imsl.datamining.neural.Network: Default constructor for Network.
Node - class com.imsl.datamining.neural.Node.: A Node in a neural network.
NonlinLeastSquares - class com.imsl.math.NonlinLeastSquares.: Nonlinear least squares.
NonlinLeastSquares(int, int) - Constructor for class com.imsl.math.NonlinLeastSquares: Creates an object to solve a nonlinear least squares problem.
NonlinLeastSquares.FalseConvergenceException - exception com.imsl.math.NonlinLeastSquares.FalseConvergenceException.: The iterates appear to be converging to a non-critical point.
NonlinLeastSquares.FalseConvergenceException(String) - Constructor for class com.imsl.math.NonlinLeastSquares.FalseConvergenceException
NonlinLeastSquares.FalseConvergenceException(String, Object[]) - Constructor for class com.imsl.math.NonlinLeastSquares.FalseConvergenceException
NonlinLeastSquares.Function - interface com.imsl.math.NonlinLeastSquares.Function.: Public interface for the user supplied function to the NonlinLeastSquares object.
NonlinLeastSquares.Jacobian - interface com.imsl.math.NonlinLeastSquares.Jacobian.: Public interface for the user supplied function to the NonlinLeastSquares object.
NonlinLeastSquares.RelativeFunctionConvergenceException - exception com.imsl.math.NonlinLeastSquares.RelativeFunctionConvergenceException.: The scaled and predicted reductions in the function are less than or equal to the relative function convergence tolerance.
NonlinLeastSquares.RelativeFunctionConvergenceException(String) - Constructor for class com.imsl.math.NonlinLeastSquares.RelativeFunctionConvergenceException
NonlinLeastSquares.RelativeFunctionConvergenceException(String, Object[]) - Constructor for class com.imsl.math.NonlinLeastSquares.RelativeFunctionConvergenceException
NonlinLeastSquares.StepMaxException - exception com.imsl.math.NonlinLeastSquares.StepMaxException.: Either the function is unbounded below, has a finite asymptote in some direction, or the maximum stepsize is too small.
NonlinLeastSquares.StepMaxException(String) - Constructor for class com.imsl.math.NonlinLeastSquares.StepMaxException
NonlinLeastSquares.StepMaxException(String, Object[]) - Constructor for class com.imsl.math.NonlinLeastSquares.StepMaxException
NonlinLeastSquares.StepToleranceException - exception com.imsl.math.NonlinLeastSquares.StepToleranceException.: Various possible errors involving the step tolerance.
NonlinLeastSquares.StepToleranceException(String) - Constructor for class com.imsl.math.NonlinLeastSquares.StepToleranceException
NonlinLeastSquares.StepToleranceException(String, Object[]) - Constructor for class com.imsl.math.NonlinLeastSquares.StepToleranceException
NonlinLeastSquares.TooManyIterationsException - exception com.imsl.math.NonlinLeastSquares.TooManyIterationsException.: Too many iterations.
NonlinLeastSquares.TooManyIterationsException() - Constructor for class com.imsl.math.NonlinLeastSquares.TooManyIterationsException
NonlinLeastSquares.TooManyIterationsException(String, Object[]) - Constructor for class com.imsl.math.NonlinLeastSquares.TooManyIterationsException
NonlinLeastSquares.TooManyIterationsException(Object[]) - Constructor for class com.imsl.math.NonlinLeastSquares.TooManyIterationsException
NonlinearRegression - class com.imsl.stat.NonlinearRegression.: Fits a multivariate nonlinear regression model using least squares.
NonlinearRegression(int) - Constructor for class com.imsl.stat.NonlinearRegression: Constructs a new nonlinear regression object.
NonlinearRegression.Derivative - interface com.imsl.stat.NonlinearRegression.Derivative.: Public interface for the user supplied function to compute the derivative for NonlinearRegression.
NonlinearRegression.Function - interface com.imsl.stat.NonlinearRegression.Function.: Public interface for the user supplied function for NonlinearRegression.
NonlinearRegression.NegativeFreqException - exception com.imsl.stat.NonlinearRegression.NegativeFreqException.: A negative frequency was encountered.
NonlinearRegression.NegativeFreqException(int, int, double) - Constructor for class com.imsl.stat.NonlinearRegression.NegativeFreqException: Constructs a NegativeFreqException.
NonlinearRegression.NegativeWeightException - exception com.imsl.stat.NonlinearRegression.NegativeWeightException.: A negative weight was encountered.
NonlinearRegression.NegativeWeightException(int, int, double) - Constructor for class com.imsl.stat.NonlinearRegression.NegativeWeightException: Constructs a NegativeWeightException.
NonlinearRegression.TooManyIterationsException - exception com.imsl.stat.NonlinearRegression.TooManyIterationsException.: The number of iterations has exceeded the maximum allowed.
NonlinearRegression.TooManyIterationsException() - Constructor for class com.imsl.stat.NonlinearRegression.TooManyIterationsException: Constructs a TooManyIterationsException.
NormOneSample - class com.imsl.stat.NormOneSample.: Computes statistics for mean and variance inferences using a sample from a normal population.
NormOneSample(double[]) - Constructor for class com.imsl.stat.NormOneSample: Constructor to compute statistics for mean and variance inferences using a sample from a normal population.
NormTwoSample - class com.imsl.stat.NormTwoSample.: Computes statistics for mean and variance inferences using samples from two normal populations.
NormTwoSample(double[], double[]) - Constructor for class com.imsl.stat.NormTwoSample: Constructor to compute statistics for mean and variance inferences using samples from two normal populations.
NormalityTest - class com.imsl.stat.NormalityTest.: Performs a test for normality.
NormalityTest(double[]) - Constructor for class com.imsl.stat.NormalityTest: Constructor for NormalityTest.
NormalityTest.NoVariationInputException - exception com.imsl.stat.NormalityTest.NoVariationInputException.: There is no variation in the input data.
NormalityTest.NoVariationInputException(String) - Constructor for class com.imsl.stat.NormalityTest.NoVariationInputException
NormalityTest.NoVariationInputException(String, Object[]) - Constructor for class com.imsl.stat.NormalityTest.NoVariationInputException
nCoef - Variable in class com.imsl.math.BsLeastSquares: Number of B-spline coefficients.
nFunctionEvaluations - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
nFunctionEvaluations - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
nObs - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
nObs - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
nY - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
nY - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
negate(Complex) - Static method in class com.imsl.math.Complex: Returns the negative of a Complex object, -z.
negate(Physical) - Static method in class com.imsl.math.Physical: Negate a Physical object.
next() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor down one row from its current position.
next(int) - Method in class com.imsl.stat.MersenneTwister: Generates the next pseudorandom number.
next(int) - Method in class com.imsl.stat.MersenneTwister64: Generates the next pseudorandom number.
next(int) - Method in interface com.imsl.stat.Random.BaseGenerator: Generates the next pseudorandom number.
next(int) - Method in class com.imsl.stat.Random: Generates the next pseudorandom number.
nextAfter(double, double) - Static method in class com.imsl.math.IEEE: Returns the next machine floating-point number next to x in the direction toward y.
nextBeta(double, double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a beta distribution.
nextBinomial(int, double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a binomial distribution.
nextCauchy() - Method in class com.imsl.stat.Random: Generates a pseudorandom number from a Cauchy distribution.
nextChiSquared(double) - Method in class com.imsl.stat.Random: Generates a pseudorandom number from a Chi-squared distribution.
nextDouble() - Method in class com.imsl.stat.FaureSequence: Returns the first value of the next point in the sequence.
nextDouble() - Method in class com.imsl.stat.MersenneTwister: Generates the next pseudorandom, uniformly distributed double value from this random number generator's sequence.
nextDouble() - Method in class com.imsl.stat.MersenneTwister64: Generates the next pseudorandom, uniformly distributed double value from this random number generator's sequence.
nextExponential() - Method in class com.imsl.stat.Random: Generates a pseudorandom number from a standard exponential distribution.
nextExponentialMix(double, double, double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a mixture of two exponential distributions.
nextExtremeValue(double, double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from an extreme value distribution.
nextF(double, double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from the F distribution.
nextFloat() - Method in class com.imsl.stat.MersenneTwister: Generates the next pseudorandom, uniformly distributed float value from this random number generator's sequence.
nextFloat() - Method in class com.imsl.stat.MersenneTwister64: Generates the next pseudorandom, uniformly distributed float value from this random number generator's sequence.
nextGamma(double) - Method in class com.imsl.stat.Random: Generates a pseudorandom number from a standard gamma distribution.
nextGeometric(double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a geometric distribution.
nextHypergeometric(int, int, int) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a hypergeometric distribution.
nextInt() - Method in class com.imsl.stat.MersenneTwister: Generates the next pseudorandom number.
nextLogNormal(double, double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a lognormal distribution.
nextLogarithmic(double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a logarithmic distribution.
nextLong() - Method in class com.imsl.stat.MersenneTwister64: Generates the next pseudorandom, uniformly distributed long value from this random number generator's sequence.
nextMultivariateNormal(int, Cholesky) - Method in class com.imsl.stat.Random: Generate pseudorandom numbers from a multivariate normal distribution.
nextNegativeBinomial(double, double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a negative binomial distribution.
nextNormal() - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a standard normal distribution using an inverse CDF method.
nextNormalAR() - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a standard normal distribution using an acceptance/rejection method.
nextPoint() - Method in class com.imsl.stat.FaureSequence: Returns the next point in the sequence.
nextPoint() - Method in interface com.imsl.stat.RandomSequence: Returns the next multidimensional point in the sequence.
nextPoisson(double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a Poisson distribution.
nextPrime(int) - Static method in class com.imsl.stat.FaureSequence: Returns the smallest prime greater than or equal to n.
nextRayleigh(double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a Rayleigh distribution.
nextStudentsT(double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a Student's t distribution.
nextToken() - Method in class com.imsl.io.Tokenizer: Returns the next token.
nextTriangular() - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a triangular distribution on the interval (0,1).
nextVonMises(double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a von Mises distribution.
nextWeibull(double) - Method in class com.imsl.stat.Random: Generate a pseudorandom number from a Weibull distribution.
node - Variable in class com.imsl.chart.Draw
nominal(double, int) - Static method in class com.imsl.finance.Finance: Returns the nominal annual interest rate.
noncentralchi(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the noncentral chi-squared cumulative probability distribution function.
noncentralstudentsT(double, int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the noncentral Student's t cumulative probability distribution function.
normal(double) - Static method in class com.imsl.stat.Cdf: Evaluates the normal (Gaussian) cumulative probability distribution function.
nper(double, double, double, double, int) - Static method in class com.imsl.finance.Finance: Returns the number of periods for an investment for which periodic, and constant payments are made and the interest rate is constant.
npv(double, double[]) - Static method in class com.imsl.finance.Finance: Returns the net present value of a stream of equal periodic cash flows, which are subject to a given discount rate.
numberFormat - Variable in class com.imsl.math.PrintMatrixFormat: The NumberFormat to be used in formatting double and Complex entries.

O

OdeRungeKutta - class com.imsl.math.OdeRungeKutta.: Solves an initial-value problem for ordinary differential equations using the Runge-Kutta-Verner fifth-order and sixth-order method.
OdeRungeKutta(OdeRungeKutta.Function) - Constructor for class com.imsl.math.OdeRungeKutta: Constructs an ODE solver to solve the initial value problem dy/dx = f(x,y)
OdeRungeKutta.DidNotConvergeException - exception com.imsl.math.OdeRungeKutta.DidNotConvergeException.: The iteration did not converge.
OdeRungeKutta.DidNotConvergeException(String) - Constructor for class com.imsl.math.OdeRungeKutta.DidNotConvergeException
OdeRungeKutta.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.math.OdeRungeKutta.DidNotConvergeException
OdeRungeKutta.Function - interface com.imsl.math.OdeRungeKutta.Function.: Public interface for user supplied function to OdeRungeKutta object.
OdeRungeKutta.ToleranceTooSmallException - exception com.imsl.math.OdeRungeKutta.ToleranceTooSmallException.: Tolerance is too small.
OdeRungeKutta.ToleranceTooSmallException(String, Object[]) - Constructor for class com.imsl.math.OdeRungeKutta.ToleranceTooSmallException
OutputLayer - class com.imsl.datamining.neural.OutputLayer.: Output layer in a neural network.
OutputPerceptron - class com.imsl.datamining.neural.OutputPerceptron.: A Perceptron in the output layer.
oneNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Return the Complex matrix one norm.
oneNorm(double[][]) - Static method in class com.imsl.math.Matrix: Return the matrix one norm.
order - Variable in class com.imsl.math.BSpline: Order of the spline.
out - Variable in class com.imsl.WarningObject: The warning stream.
outline - Static variable in class com.imsl.chart.Draw: Markers defined on a [-1,1] x [-1,1] grid.

P

PARSE_BYTE - Static variable in class com.imsl.io.FlatFile: Implements a Parser that converts a String to a Byte.
PARSE_DOUBLE - Static variable in class com.imsl.io.FlatFile: Implements a Parser that converts a String to a Double.
PARSE_FLOAT - Static variable in class com.imsl.io.FlatFile: Implements a Parser that converts a String to a Float.
PARSE_INTEGER - Static variable in class com.imsl.io.FlatFile: Implements a Parser that converts a String to a Integer.
PARSE_LONG - Static variable in class com.imsl.io.FlatFile: Implements a Parser that converts a String to a Long.
PARSE_SHORT - Static variable in class com.imsl.io.FlatFile: Implements a Parser that converts a String to a Short.
PI - Static variable in class com.imsl.math.JMath
POOLED - Static variable in class com.imsl.stat.DiscriminantAnalysis: Indicates Pooled covariances computed.
POOLED_GROUP - Static variable in class com.imsl.stat.DiscriminantAnalysis: Indicates Pooled, group covariances computed.
POOL_INTERACTIONS - Static variable in class com.imsl.stat.ANOVAFactorial: Indicates factor nSubscripts is not error.
PRINCIPAL_COMPONENT_MODEL - Static variable in class com.imsl.stat.FactorAnalysis: Indicates principal component model.
PRINCIPAL_FACTOR_MODEL - Static variable in class com.imsl.stat.FactorAnalysis: Indicates principal factor model.
PRIOR_EQUAL - Static variable in class com.imsl.stat.DiscriminantAnalysis: Indicates prior probability type is to be prior equal.
PRIOR_PROPORTIONAL - Static variable in class com.imsl.stat.DiscriminantAnalysis: Indicates prior probability type is to be prior proportional.
PRISM - Static variable in interface com.imsl.chart.Colormap: Prism colormap.
PURE_ERROR - Static variable in class com.imsl.stat.ANOVAFactorial: Indicates factor nSubscripts is error.
Perceptron - class com.imsl.datamining.neural.Perceptron.: A Perceptron node in a neural network.
Physical - class com.imsl.math.Physical.: Return the value of various mathematical and physical constants.
Physical() - Constructor for class com.imsl.math.Physical: Constructs a new 0-valued, dimensionless object.
Physical(Physical) - Constructor for class com.imsl.math.Physical: Constructs a copy of a Physical object.
Physical(double, String) - Constructor for class com.imsl.math.Physical: Constructs a new Physical object and initializes this object to a double value.
Physical(double, int, int, int, int, int) - Constructor for class com.imsl.math.Physical: Constructs a new Physical object and initializes this object to a double value along with int values for length, mass, time, current, and temperature.
PickEvent - class com.imsl.chart.PickEvent.: An event that indicates that a chart element has been selected.
PickEvent(MouseEvent) - Constructor for class com.imsl.chart.PickEvent: Construct a PickEvent object.
PickEvent(Component, int, long, int, int, int, int, boolean) - Constructor for class com.imsl.chart.PickEvent: Construct a PickEvent object at point (x,y).
PickListener - interface com.imsl.chart.PickListener.: The listener interface for receiving pick events.
Pie - class com.imsl.chart.Pie.: A pie chart.
Pie(Chart) - Constructor for class com.imsl.chart.Pie: Constructs a Pie chart object.
Pie(Chart, double[]) - Constructor for class com.imsl.chart.Pie: Constructs a Pie chart object with a specified number of slices.
PieSlice - class com.imsl.chart.PieSlice.: One wedge of a pie chart.
PointLight - class com.imsl.chart3d.PointLight.: A point light source.
PointLight(Chart3D) - Constructor for class com.imsl.chart3d.PointLight: Creates a point light source at the origin.
PointLight(Chart3D, double, double, double) - Constructor for class com.imsl.chart3d.PointLight: Creates a point light at a specified position.
Polar - class com.imsl.chart.Polar.: This Axis node is used for polar charts.
Polar(Chart) - Constructor for class com.imsl.chart.Polar: Create an AxisPolar.
PrintMatrix - class com.imsl.math.PrintMatrix.: Matrix printing utilities.
PrintMatrix() - Constructor for class com.imsl.math.PrintMatrix: Creates an instance of the PrintMatrix class.
PrintMatrix(PrintStream) - Constructor for class com.imsl.math.PrintMatrix: Creates an instance of the PrintMatrix class with the specified PrintStream.
PrintMatrix(String) - Constructor for class com.imsl.math.PrintMatrix: Creates a PrintMatrix object and sets its title.
PrintMatrix(PrintStream, String) - Constructor for class com.imsl.math.PrintMatrix: Creates a PrintMatrix object with the specified PrintStream and sets its title.
PrintMatrixFormat - class com.imsl.math.PrintMatrixFormat.: This class can be used to customize the actions of PrintMatrix.
PrintMatrixFormat() - Constructor for class com.imsl.math.PrintMatrixFormat: Constructs a PrintMatrixFormat object.
paint(Draw) - Method in class com.imsl.chart.Axis: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Axis1D: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisLabel: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisLine: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisR: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisRLabel: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisRLine: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisRMajorTick: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisTheta: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisTitle: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisUnit: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisXY: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Background: Paint this node.
paint(Draw) - Method in class com.imsl.chart.Bar: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.BarItem: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.BarSet
paint(Draw) - Method in class com.imsl.chart.BoxPlot: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Candlestick: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.CandlestickItem: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Chart: Paints this node and all of its children.
paint(Graphics) - Method in class com.imsl.chart.Chart: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.ChartNode: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.ChartTitle: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Contour.Legend: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Contour
paint(Draw) - Method in class com.imsl.chart.ContourLevel: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Data: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Dendrogram: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.ErrorBar: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Grid: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.GridPolar: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Heatmap.Legend: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Heatmap: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.HighLowClose: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Legend: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.MajorTick: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.MinorTick: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.PieSlice: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Polar: Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.ToolTip: Paints this node and all of its children.
paint(Graphics) - Method in class com.imsl.chart3d.BufferedPaint: Paint the image onto the canvas.
paint(Graphics) - Method in interface com.imsl.chart3d.Canvas3DChart.Paint
paint(Graphics) - Method in class com.imsl.chart3d.Canvas3DChart: Paint method overriden to correct a problem in JDK 1.4.
paintChart(Graphics) - Method in class com.imsl.chart.Chart: Draw the chart using the given Graphics object.
paintComponent(Graphics) - Method in class com.imsl.chart.JPanelChart: Calls the UI delegate's paint method, if the UI delegate is non-null.
paintImage() - Method in class com.imsl.chart.Chart: Returns an Image of the chart.
parse(String) - Method in interface com.imsl.io.FlatFile.Parser: Parse a String into an Object.
parse(String) - Method in class com.imsl.io.Tokenizer: Sets the line to be tokenized.
parseColor(String) - Static method in class com.imsl.chart.AbstractChartNode: Returns a color specified by name or a red-green-blue triple.
path - Variable in class com.imsl.chart.Draw
performanceIndex(double[][]) - Method in class com.imsl.math.Eigen: Returns the performance index of a real eigensystem.
performanceIndex(double[][]) - Method in class com.imsl.math.SymEigen: Returns the performance index of a real symmetric eigensystem.
pick(MouseEvent) - Method in class com.imsl.chart.Chart: Fire the PickListeners for the nodes hit by the event.
pickNode() - Method in class com.imsl.chart.DrawPick: Register the currentNode as the "picked" node if the "PickListener" attribute is defined for the current node.
pickPerformed(PickEvent) - Method in interface com.imsl.chart.PickListener: Public interface for PickListener.
pickPerformed(PickEvent) - Method in class com.imsl.chart.ToolTip: Part of the PickListener interface.
pmt(double, int, double, double, int) - Static method in class com.imsl.finance.Finance: Returns the periodic payment for an investment.
poch(double, double) - Static method in class com.imsl.math.Sfun: Returns a generalization of Pochhammer's symbol.
pointToLine(int, int, int[], int[]) - Static method in class com.imsl.chart.PickEvent: Compute the distance from the point (Px,Py) to the line segment AB.
poisson(int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the Poisson cumulative probability distribution function.
poissonProb(int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the Poisson probability density function.
poly(int[], int[]) - Method in class com.imsl.chart.DrawMap: Sets a polygon as the target.
postRender() - Method in class com.imsl.chart3d.Canvas3DChart: Calls the Paint objects added to the post-render list.
postSwap() - Method in class com.imsl.chart3d.Canvas3DChart: Writes the chart to a file as a bitmap image.
pow(Complex, double) - Static method in class com.imsl.math.Complex: Returns the Complex z raised to the x power, with a branch cut for the first parameter (z) along the negative real axis.
pow(Complex, Complex) - Static method in class com.imsl.math.Complex: Returns the Complex x raised to the Complex y power.
pow(double, double) - Static method in class com.imsl.math.JMath: Returns x to the power y.
ppmt(double, int, int, double, double, int) - Static method in class com.imsl.finance.Finance: Returns the payment on the principal for a specified period.
preRender() - Method in class com.imsl.chart3d.Canvas3DChart: Calls the Paint objects added to the pre-render list.
predictedClass(double[]) - Method in class com.imsl.datamining.neural.BinaryClassification: Calculates the classification probablities for the input pattern x, and returns either 0 or 1 identifying the class with the highest probability.
predictedClass(double[]) - Method in class com.imsl.datamining.neural.MultiClassification: Calculates the classification probablities for the input pattern x, and returns the class with the highest probability.
previous() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the previous row in this ResultSet object.
price(GregorianCalendar, GregorianCalendar, double, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the price, per $100 face value, of a security that pays periodic interest.
pricedisc(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the price of a discount bond given the discount rate.
pricemat(GregorianCalendar, GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the price, per $100 face value, of a discount bond.
priceyield(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the price of a discount bond given the yield.
print(Object, String, String, Object[]) - Static method in class com.imsl.Warning: Issue a warning message.
print(Object, String, String, Object[]) - Method in class com.imsl.WarningObject: Issue a warning message.
print(Graphics, PageFormat, int) - Method in class com.imsl.chart.Chart: This method implements the Printable interface.
print() - Method in class com.imsl.chart.JPanelChart: Print the chart, centered on a page.
print(String) - Method in class com.imsl.math.PrintMatrix: Print a string.
print(Object) - Method in class com.imsl.math.PrintMatrix: Prints an nRows by nColumns matrix with specified format.
print(PrintMatrixFormat, Object) - Method in class com.imsl.math.PrintMatrix: Prints an nRows by nColumns matrix with specified format.
printHTML(PrintMatrixFormat, Object, int, int) - Method in class com.imsl.math.PrintMatrix: Prints an nRows by nColumns matrix with specified format for HTML output.
println() - Method in class com.imsl.math.PrintMatrix: Print a newline.
probabilities(double[]) - Method in class com.imsl.datamining.neural.BinaryClassification: Returns classification probabilities for the input pattern x.
probabilities(double[]) - Method in class com.imsl.datamining.neural.MultiClassification: Returns classification probabilities for the input pattern x.
processCommand(String, String) - Method in class com.imsl.io.MPSReader: Process a section of the MPS file.
pv(double, int, double, double, int) - Static method in class com.imsl.finance.Finance: Returns the net present value of a stream of equal periodic cash flows, which are subject to a given discount rate.

Q

QR - class com.imsl.math.QR.: QR Decomposition of a matrix.
QR(double[][]) - Constructor for class com.imsl.math.QR: Constructs the QR decomposition of a matrix with elements of type double.
QUADRATIC - Static variable in class com.imsl.stat.DiscriminantAnalysis: Indicates a quadratic discrimination method.
QUARTERLY - Static variable in class com.imsl.finance.Bond: Coupon payments are made quarterly.
QuadraticProgramming - class com.imsl.math.QuadraticProgramming.: Solves the convex quadratic programming problem subject to equality or inequality constraints.
QuadraticProgramming(double[][], double[], double[][], double[], double[][], double[]) - Constructor for class com.imsl.math.QuadraticProgramming: Solve a quadratic programming problem.
QuadraticProgramming.InconsistentSystemException - exception com.imsl.math.QuadraticProgramming.InconsistentSystemException.: Inconsistent system.
QuadraticProgramming.InconsistentSystemException() - Constructor for class com.imsl.math.QuadraticProgramming.InconsistentSystemException
Quadrature - class com.imsl.math.Quadrature.: Quadrature is a general-purpose integrator that uses a globally adaptive scheme in order to reduce the absolute error.
Quadrature() - Constructor for class com.imsl.math.Quadrature: Constructs a Quadrature object.
Quadrature.Function - interface com.imsl.math.Quadrature.Function.: Public interface function for the Quadrature class.
QuasiNewtonTrainer - class com.imsl.datamining.neural.QuasiNewtonTrainer.: Trains a network using the quasi-Newton method, MinUnconMultiVar.
QuasiNewtonTrainer() - Constructor for class com.imsl.datamining.neural.QuasiNewtonTrainer: Constructs a QuasiNewtonTrainer object.
QuasiNewtonTrainer.BlockGradObjective - class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective.
QuasiNewtonTrainer.BlockGradObjective() - Constructor for class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective
QuasiNewtonTrainer.BlockObjective - class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockObjective.
QuasiNewtonTrainer.BlockObjective() - Constructor for class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockObjective
QuasiNewtonTrainer.Error - interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error.: Error function to be minimized by trainer.
QuasiNewtonTrainer.GradObjective - class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective.: The Objective class is passed to the optimizer.
QuasiNewtonTrainer.Objective - class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective.: The Objective class is passed to the optimizer.

R

RADIAN - Static variable in class com.imsl.chart.Draw
RECLASSIFICATION - Static variable in class com.imsl.stat.DiscriminantAnalysis: Indicates reclassification as the classicfication method.
RED - Static variable in interface com.imsl.chart.Colormap: Linear red colormap.
RED_PURPLE - Static variable in interface com.imsl.chart.Colormap: Red/purple colormap.
RED_TEMPERATURE - Static variable in interface com.imsl.chart.Colormap: Red temperature colormap.
ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatted string for a given row label is to be returned.
R_SQUARED_CRITERION - Static variable in class com.imsl.stat.SelectionRegression: Indicates criterion regression.
RadialBasis - class com.imsl.math.RadialBasis.: RadialBasis computes a least-squares fit to scattered data in ${bf R}^d$ , where d is the dimension.
RadialBasis(int, int) - Constructor for class com.imsl.math.RadialBasis: Creates a new instance of RadialBasis.
RadialBasis.Function - interface com.imsl.math.RadialBasis.Function.: Public interface for the user supplied function to the RadialBasis object.
RadialBasis.Gaussian - class com.imsl.math.RadialBasis.Gaussian.: The Gaussian basis function, $e^{-ax^2}$ .
RadialBasis.Gaussian(double) - Constructor for class com.imsl.math.RadialBasis.Gaussian
RadialBasis.HardyMultiquadric - class com.imsl.math.RadialBasis.HardyMultiquadric.: The Hardy multiquadric basis function, $sqrt{r^2+delta^2}$ .
RadialBasis.HardyMultiquadric(double) - Constructor for class com.imsl.math.RadialBasis.HardyMultiquadric: Creates a Hardy multiquadric basis function.
Random - class com.imsl.stat.Random.: Generate uniform and non-uniform random number distributions.
Random() - Constructor for class com.imsl.stat.Random: Constructor for the Random number generator class.
Random(long) - Constructor for class com.imsl.stat.Random: Constructor for the Random number generator class with supplied seed.
Random(Random.BaseGenerator) - Constructor for class com.imsl.stat.Random: Constructor for the Random number generator class with an alternate basic number generator.
Random.BaseGenerator - interface com.imsl.stat.Random.BaseGenerator.: Base pseudorandom number.
RandomSequence - interface com.imsl.stat.RandomSequence.: Interface implemented by generators of random or quasi-random multidimension sequences.
Ranks - class com.imsl.stat.Ranks.: Compute the ranks, normal scores, or exponential scores for a vector of observations.
Ranks() - Constructor for class com.imsl.stat.Ranks: Constructor for the Ranks class.
Rayleigh(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the Rayleigh cumulative probability distribution function.
RayleighProb(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the Rayleigh probability density function.
RegressionBasis - interface com.imsl.stat.RegressionBasis.: Public interface for user supplied function to UserBasisRegression object.
r9lgmc(double) - Static method in class com.imsl.math.Sfun: Returns the log gamma correction term for argument values greater than or equal to 10.0.
random() - Static method in class com.imsl.math.JMath: Returns a random number from a uniform distribution.
rank(double) - Method in class com.imsl.math.QR: Returns the rank of the matrix given an input tolerance.
rate(int, double, double, double, int) - Static method in class com.imsl.finance.Finance: Returns the interest rate per period of an annuity.
rate(int, double, double, double, int, double) - Static method in class com.imsl.finance.Finance: Returns the interest rate per period of an annuity with an initial guess.
read(Reader) - Method in class com.imsl.io.MPSReader: Reads and parses the MPS file.
readLine() - Method in class com.imsl.io.FlatFile: Reads and returns a line from the input.
real() - Method in class com.imsl.math.Complex: Returns the real part of a Complex object.
real(Complex) - Static method in class com.imsl.math.Complex: Returns the real part of a Complex object.
received(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the amount one receives when a fully invested security reaches the maturity date.
rect(int, int, int, int) - Method in class com.imsl.chart.DrawMap: Sets a rectangle as the target.
refreshRow() - Method in class com.imsl.io.AbstractFlatFile: Refreshes the current row with its most recent value in the database.
registerChart(Chart, HttpServletRequest) - Method in class com.imsl.chart.JspBean: Saves the chart and sets the chart attribute "Size".
relative(int) - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor a relative number of rows, either positive or negative.
remove() - Method in class com.imsl.chart.AbstractChartNode: Removes the node from its parents list of children.
remove(Link) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Removes a Link from the network.
removePickListener(PickListener) - Method in class com.imsl.chart.ChartNode: Removes a PickListener from this node.
removePostRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart: Removes a Paint object from the list of post-render Paint objects.
removePreRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart: Removes a Paint object from the list of pre-render Paint objects.
render() - Method in class com.imsl.chart3d.Canvas3DChart: Creates a scene graph from the chart tree and starts rendering the scene graph into this canvas.
render() - Method in class com.imsl.chart3d.JFrameChart3D: Renders the 3D chart node tree into a Java 3D scene graph.
repaint() - Method in class com.imsl.chart.Chart: Prepares the chart to be repainted by deleting any double buffering image.
resetViewPlatformTransformation() - Method in class com.imsl.chart3d.Chart3D: Resets the view platform transformation to its default value.
rint(double) - Static method in class com.imsl.math.JMath: Returns the value of a double rounded toward the closest integral value.
round(float) - Static method in class com.imsl.math.JMath: Returns the integer closest to a given float.
round(double) - Static method in class com.imsl.math.JMath: Returns the long closest to a given double.
rowDeleted() - Method in class com.imsl.io.AbstractFlatFile: Indicates whether a row has been deleted.
rowInserted() - Method in class com.imsl.io.AbstractFlatFile: Indicates whether the current row has had an insertion.
rowUpdated() - Method in class com.imsl.io.AbstractFlatFile: Indicates whether the current row has been updated.

S

SECOND_DERIVATIVE - Static variable in class com.imsl.math.CsInterpolate
SEMIANNUAL - Static variable in class com.imsl.finance.Bond: Coupon payments are made semiannually.
SOFTMAX - Static variable in interface com.imsl.datamining.neural.Activation: The softmax activation function.
SPECTRAL - Static variable in interface com.imsl.chart.Colormap: Spectral colormap.
SQUASH - Static variable in interface com.imsl.datamining.neural.Activation: The squash activation function, $g(x) = frac{x}{1+|x|}$
STANDARD_GAMMA - Static variable in interface com.imsl.chart.Colormap: Standard gamma colormap.
STDEV_CORRELATION_MATRIX - Static variable in class com.imsl.stat.Covariances: Indicates correlation matrix except for the diagonal elements which are the standard deviations
STEPWISE_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression: Indicates stepwise regression.
STRICT_LOWER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix: This flag as the argument to setMatrixType, indicates that only the strict lower triangular elements of the matrix are to be printed.
STRICT_UPPER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix: This flag as the argument to setMatrixType, indicates that only the strict upper triangular elements of the matrix are to be printed.
SUM_OF_SQUARES - Static variable in class com.imsl.datamining.neural.QuasiNewtonTrainer: Compute the sum of squares error.
SURFACE_TYPE_FLAT - Static variable in class com.imsl.chart3d.Surface: Draws the surface using flat shading.
SURFACE_TYPE_GOURAUD - Static variable in class com.imsl.chart3d.Surface: Draws the surface using Gouraud shading.
SURFACE_TYPE_MESH - Static variable in class com.imsl.chart3d.Surface: Draws the surface as a mesh.
SURFACE_TYPE_NICEST - Static variable in class com.imsl.chart3d.Surface: Draws the surface using the best shading available.
SVD - class com.imsl.math.SVD.: Singular Value Decomposition (SVD) of a rectangular matrix of type double.
SVD(double[][], double) - Constructor for class com.imsl.math.SVD: Construct the singular value decomposition of a rectangular matrix with a given tolerance.
SVD(double[][]) - Constructor for class com.imsl.math.SVD: Construct the singular value decomposition of a rectangular matrix with default tolerance.
SVD.DidNotConvergeException - exception com.imsl.math.SVD.DidNotConvergeException.: The iteration did not converge
SVD.DidNotConvergeException(String) - Constructor for class com.imsl.math.SVD.DidNotConvergeException
SVD.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.math.SVD.DidNotConvergeException
ScaleFilter - class com.imsl.datamining.neural.ScaleFilter.: Scales or unscales continuous data prior to its use in neural network training, testing, or forecasting.
ScaleFilter(int) - Constructor for class com.imsl.datamining.neural.ScaleFilter: Constructor for ScaleFilter.
SelectionRegression - class com.imsl.stat.SelectionRegression.: Selects the best multiple linear regression models.
SelectionRegression(int) - Constructor for class com.imsl.stat.SelectionRegression: Constructs a new SelectionRegression object.
SelectionRegression.NoVariablesException - exception com.imsl.stat.SelectionRegression.NoVariablesException.: No Variables can enter the model.
SelectionRegression.NoVariablesException() - Constructor for class com.imsl.stat.SelectionRegression.NoVariablesException: Constructs a NoVariablesException.
SelectionRegression.Statistics - class com.imsl.stat.SelectionRegression.Statistics.: Statistics contains statistics related to the regression coefficients.
Sfun - class com.imsl.math.Sfun.: Collection of special functions.
ShapiroWilkWTest() - Method in class com.imsl.stat.NormalityTest: Performs the Shapiro-Wilk W test.
SignTest - class com.imsl.stat.SignTest.: Performs a sign test.
SignTest(double[]) - Constructor for class com.imsl.stat.SignTest: Constructor for SignTest.
SingularMatrixException - exception com.imsl.math.SingularMatrixException.: The matrix is singular.
SingularMatrixException() - Constructor for class com.imsl.math.SingularMatrixException
Sort - class com.imsl.stat.Sort.: A collection of sorting functions.
Sort() - Constructor for class com.imsl.stat.Sort
Spline - class com.imsl.math.Spline.: Spline represents and evaluates univariate piecewise polynomial splines.
Spline() - Constructor for class com.imsl.math.Spline
SplineData - class com.imsl.chart.SplineData.: A data set created from a Spline.
SplineData(ChartNode, Spline) - Constructor for class com.imsl.chart.SplineData: Creates a data node from Spline values.
StepwiseRegression - class com.imsl.stat.StepwiseRegression.: Builds multiple linear regression models using forward selection, backward selection, or stepwise selection.
StepwiseRegression(double[][], double[]) - Constructor for class com.imsl.stat.StepwiseRegression: Creates a new instance of StepwiseRegression.
StepwiseRegression(double[][], double[], double[]) - Constructor for class com.imsl.stat.StepwiseRegression: Creates a new instance of weighted StepwiseRegression.
StepwiseRegression(double[][], double[], double[], double[]) - Constructor for class com.imsl.stat.StepwiseRegression: Creates a new instance of weighted StepwiseRegression using observation frequencies.
StepwiseRegression(double[][], int) - Constructor for class com.imsl.stat.StepwiseRegression: Creates a new instance of StepwiseRegression from a user-supplied variance-covariance matrix.
StepwiseRegression.CoefficientTTests - class com.imsl.stat.StepwiseRegression.CoefficientTTests.: CoefficientTTests contains statistics related to the student-t test, for each regression coefficient.
StepwiseRegression.CyclingIsOccurringException - exception com.imsl.stat.StepwiseRegression.CyclingIsOccurringException.: Cycling is occurring.
StepwiseRegression.CyclingIsOccurringException(int) - Constructor for class com.imsl.stat.StepwiseRegression.CyclingIsOccurringException: Constructs a CyclingIsOccurringException.
StepwiseRegression.NoVariablesEnteredException - exception com.imsl.stat.StepwiseRegression.NoVariablesEnteredException.: No Variables can enter the model.
StepwiseRegression.NoVariablesEnteredException() - Constructor for class com.imsl.stat.StepwiseRegression.NoVariablesEnteredException: Constructs a NoVariablesEnteredException.
Summary - class com.imsl.stat.Summary.: Computes basic univariate statistics.
Summary() - Constructor for class com.imsl.stat.Summary: Constructs a new summary statistics object.
Surface - class com.imsl.chart3d.Surface.: Surface from a function or from a set of scattered data points.
Surface(AxisXYZ, Surface.ZFunction, double, double, double, double) - Constructor for class com.imsl.chart3d.Surface: Creates a surface from a function.
Surface(AxisXYZ, double[], double[], double[][]) - Constructor for class com.imsl.chart3d.Surface: Creates a surface from a gridded data set.
Surface(AxisXYZ, double[], double[], double[][], Color[][]) - Constructor for class com.imsl.chart3d.Surface: Creates a colored surface from a gridded data set.
Surface(AxisXYZ, double[], double[], double[]) - Constructor for class com.imsl.chart3d.Surface: Creates a surface from a scattered set of 3D points.
Surface(AxisXYZ, double[], double[], double[], Color[]) - Constructor for class com.imsl.chart3d.Surface: Creates a surface from a scattered set of 3D points with a color given at each point.
Surface.ZFunction - interface com.imsl.chart3d.Surface.ZFunction.: Functional representation of a surface.
SymEigen - class com.imsl.math.SymEigen.: Computes the eigenvalues and eigenvectors of a real symmetric matrix.
SymEigen(double[][]) - Constructor for class com.imsl.math.SymEigen: Constructs the eigenvalues and the eigenvectors for a real symmetric matrix.
SymEigen(double[][], boolean) - Constructor for class com.imsl.math.SymEigen: Constructs the eigenvalues and (optionally) the eigenvectors for a real symmetric matrix.
sampleStandardDeviation(double[]) - Static method in class com.imsl.stat.Summary: Returns the sample standard deviation of the given data set.
sampleStandardDeviation(double[], double[]) - Static method in class com.imsl.stat.Summary: Returns the sample standard deviation of the given data set and associated weights.
sampleVariance(double[]) - Static method in class com.imsl.stat.Summary: Returns the sample variance of the given data set.
sampleVariance(double[], double[]) - Static method in class com.imsl.stat.Summary: Returns the sample variance of the given data set and associated weights.
saveChart(Chart, HttpServletRequest) - Method in class com.imsl.chart.JspBean: Saves the chart so that a servlet can later render it.
scalbn(double, int) - Static method in class com.imsl.math.IEEE: Returns 2ⁿ computed by exponent manipulation rather than by actually performing an exponentiation or a multiplication.
scaleFont - Variable in class com.imsl.chart.Draw
scaledK(double, double, int) - Static method in class com.imsl.math.Bessel: Evaluate a sequence of exponentially scaled modified Bessel functions of the third kind with fractional order and real argument.
serialVersionUID - Static variable in class com.imsl.chart.AbstractChartNode
serialVersionUID - Static variable in class com.imsl.chart.AxisR
serialVersionUID - Static variable in class com.imsl.chart.AxisRLabel
serialVersionUID - Static variable in class com.imsl.chart.AxisRLine
serialVersionUID - Static variable in class com.imsl.chart.AxisRMajorTick
serialVersionUID - Static variable in class com.imsl.chart.AxisTheta
serialVersionUID - Static variable in class com.imsl.chart.BoxPlot.Statistics
serialVersionUID - Static variable in class com.imsl.chart.BoxPlot
serialVersionUID - Static variable in class com.imsl.chart.Candlestick
serialVersionUID - Static variable in class com.imsl.chart.CandlestickItem
serialVersionUID - Static variable in class com.imsl.chart.ChartServlet
serialVersionUID - Static variable in class com.imsl.chart.Contour.Legend
serialVersionUID - Static variable in class com.imsl.chart.Contour
serialVersionUID - Static variable in class com.imsl.chart.ContourLevel
serialVersionUID - Static variable in class com.imsl.chart.Dendrogram
serialVersionUID - Static variable in class com.imsl.chart.GridPolar
serialVersionUID - Static variable in class com.imsl.chart.Heatmap.Legend
serialVersionUID - Static variable in class com.imsl.chart.Heatmap
serialVersionUID - Static variable in class com.imsl.chart.HighLowClose
serialVersionUID - Static variable in class com.imsl.chart.JFrameChart
serialVersionUID - Static variable in class com.imsl.chart.JPanelChart
serialVersionUID - Static variable in class com.imsl.chart.JspBean
serialVersionUID - Static variable in class com.imsl.chart3d.AmbientLight
serialVersionUID - Static variable in class com.imsl.chart3d.Axis3D
serialVersionUID - Static variable in class com.imsl.chart3d.AxisBox
serialVersionUID - Static variable in class com.imsl.chart3d.AxisLabel
serialVersionUID - Static variable in class com.imsl.chart3d.AxisLine
serialVersionUID - Static variable in class com.imsl.chart3d.AxisTitle
serialVersionUID - Static variable in class com.imsl.chart3d.AxisXYZ
serialVersionUID - Static variable in class com.imsl.chart3d.Background
serialVersionUID - Static variable in class com.imsl.chart3d.Chart3D
serialVersionUID - Static variable in class com.imsl.chart3d.ChartLights
serialVersionUID - Static variable in class com.imsl.chart3d.ChartNode3D
serialVersionUID - Static variable in class com.imsl.chart3d.ColormapLegend
serialVersionUID - Static variable in class com.imsl.chart3d.Data
serialVersionUID - Static variable in class com.imsl.chart3d.DirectionalLight
serialVersionUID - Static variable in class com.imsl.chart3d.JFrameChart3D
serialVersionUID - Static variable in class com.imsl.chart3d.MajorTick
serialVersionUID - Static variable in class com.imsl.chart3d.PointLight
serialVersionUID - Static variable in class com.imsl.chart3d.Surface
serialVersionUID - Static variable in interface com.imsl.datamining.neural.Activation
serialVersionUID - Static variable in class com.imsl.datamining.neural.HiddenLayer
serialVersionUID - Static variable in class com.imsl.datamining.neural.InputLayer
serialVersionUID - Static variable in class com.imsl.datamining.neural.Layer
serialVersionUID - Static variable in class com.imsl.datamining.neural.OutputLayer
serialVersionUID - Static variable in class com.imsl.datamining.neural.Perceptron
serialVersionUID - Static variable in class com.imsl.io.MPSReader.Element
serialVersionUID - Static variable in class com.imsl.io.MPSReader.Row
serialVersionUID - Static variable in class com.imsl.math.DenseLP.NoAcceptablePivotException
serialVersionUID - Static variable in class com.imsl.math.DenseLP.ProblemUnboundedException
serialVersionUID - Static variable in class com.imsl.math.LinearProgramming.ProblemInfeasibleException
serialVersionUID - Static variable in class com.imsl.math.LinearProgramming.ProblemUnboundedException
serialVersionUID - Static variable in class com.imsl.math.MinConNLP
serialVersionUID - Static variable in class com.imsl.math.RadialBasis
serialVersionUID - Static variable in class com.imsl.stat.FaureSequence
serialVersionUID - Static variable in class com.imsl.stat.KaplanMeierECDF
serialVersionUID - Static variable in class com.imsl.stat.LinearRegression.CoefficientTTests
serialVersionUID - Static variable in class com.imsl.stat.StepwiseRegression.CoefficientTTests
serialVersionUID - Static variable in class com.imsl.stat.TableMultiWay
setALT(String) - Method in class com.imsl.chart.ChartNode: Sets the value of the "ALT" attribute.
setARLags(int[]) - Method in class com.imsl.stat.ARMA: Sets the order of the autoregressive parameters.
setAbsoluteError(double) - Method in class com.imsl.math.HyperRectangleQuadrature: Sets the absolute error tolerance.
setAbsoluteError(double) - Method in class com.imsl.math.Quadrature: Sets the absolute error tolerance.
setAbsoluteError(double) - Method in class com.imsl.math.ZeroFunction: Sets first stopping criterion.
setAbsoluteFcnTol(double) - Method in class com.imsl.math.BoundedLeastSquares: Sets the absolute function tolerance.
setAbsoluteTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares: Set the absolute function tolerance.
setAbsoluteTolerance(double) - Method in class com.imsl.stat.NonlinearRegression: Sets the absolute function tolerance.
setAccuracy(double) - Method in class com.imsl.math.MinUncon: Set the required absolute accuracy in the final value returned by member function computeMin.
setActivation(Activation) - Method in class com.imsl.datamining.neural.Perceptron: Sets the activation function.
setAlignment(int) - Method in class com.imsl.chart.Text: Sets the alignment for this Text object.
setAlpha(double) - Method in class com.imsl.stat.MultipleComparisons: Sets the significance level of the test
setAngles(double, double) - Method in class com.imsl.chart.PieSlice: Sets the angles, in degrees, that determine the extent of this slice.
setAttribute(String, Object) - Method in class com.imsl.chart.AbstractChartNode: Sets an attribute.
setAutoscaleInput(int) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "AutoscaleInput" attribute.
setAutoscaleMinimumTimeInterval(int) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "AutoscaleMinimumTimeInterval" attribute.
setAutoscaleOutput(int) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "AutoscaleOutput" attribute.
setAxisTitlePosition(int) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "AxisTitlePosition" attribute.
setBackcasting(int, double) - Method in class com.imsl.stat.ARMA: Sets backcasting option.
setBackwardOrigin(int) - Method in class com.imsl.stat.ARMA: Sets the maximum backward origin.
setBarData(double[][][]) - Method in class com.imsl.chart.Bar: Convenience routine to set the "BarData" attribute.
setBarGap(double) - Method in class com.imsl.chart.ChartNode: Sets the value of the "BarGap" attribute.
setBarType(int) - Method in class com.imsl.chart.ChartNode: Sets the value of the "BarType" attribute.
setBarWidth(double) - Method in class com.imsl.chart.ChartNode: Sets the value of the "BarWidth" attribute.
setBias(double) - Method in class com.imsl.datamining.neural.Perceptron: Sets the bias for this perceptron.
setBindingThreshold(double) - Method in class com.imsl.math.MinConNLP: Set the binding threshold for constraints.
setBound(double) - Method in class com.imsl.math.MinUncon: Set the amount by which X may be changed from its initial value, xguess.
setBoundViolationBound(double) - Method in class com.imsl.math.MinConNLP: Set the amount by which bounds may be violated during numerical differentiation.
setBoundingSphere(BoundingSphere) - Method in class com.imsl.chart3d.ChartNode3D: Sets the spherical bounding region object BoundingSphere.
setBounds(double, double, double, double) - Method in class com.imsl.datamining.neural.ScaleFilter: Sets bounds to be used during bounded scaling and unscaling.
setBoxPlotType(int) - Method in class com.imsl.chart.BoxPlot: Sets the "BoxPlotType" attribute value.
setCanvas(Canvas3D) - Method in class com.imsl.chart3d.Chart3D
setCensor(int[]) - Static method in class com.imsl.stat.KaplanMeierECDF: Set flags to note right-censoring
setCensorColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the column number in x which contains the interval type for each observation.
setCenter(double) - Method in class com.imsl.datamining.neural.ScaleFilter: Set the measure of center to be used during z-score scaling.
setCenter(boolean) - Method in class com.imsl.stat.ARMA: Sets center option.
setChart(Chart) - Method in class com.imsl.chart.JFrameChart: Sets the chart to be handled.
setChart(Chart) - Method in class com.imsl.chart.JPanelChart: Sets the Chart to be handled by this container.
setChartServletName(String) - Method in class com.imsl.chart.JspBean: Sets the URL of the servlet used to render the chart.
setChartTitle(ChartTitle) - Method in class com.imsl.chart.ChartNode: Sets the value of the "ChartTitle" attribute.
setChiSquaredTestNull(double) - Method in class com.imsl.stat.NormOneSample: Sets the null hypothesis value for the chi-squared test.
setChiSquaredTestNull(double) - Method in class com.imsl.stat.NormTwoSample: Sets the null hypothesis value for the chi-squared test.
setClassificationMethod(int) - Method in class com.imsl.stat.DiscriminantAnalysis: Sets the classification method.
setClassificationVariableColumn(int[]) - Method in class com.imsl.stat.CategoricalGenLinModel: Initializes an index vector to contain the column numbers in x that are classification variables.
setClip(Rectangle) - Method in class com.imsl.chart.Draw: Set the clipping rectangle.
setClipData(boolean) - Method in class com.imsl.chart.ChartNode: Sets the value of the "ClipData" attribute.
setClose(double[]) - Method in class com.imsl.chart.HighLowClose: Sets the attribute "Close".
setColorFunction(ColorFunction) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "ColorFunction" attribute.
setColormap(Colormap) - Method in class com.imsl.chart.Heatmap: Sets the value of the "Colormap" attribute.
setColumnClass(int, Class) - Method in class com.imsl.io.AbstractFlatFile: Sets a column class.
setColumnClass(int, Class) - Method in class com.imsl.io.FlatFile
setColumnLabels(String[]) - Method in class com.imsl.math.PrintMatrixFormat: Turns on column labeling using the given labels.
setColumnName(int, String) - Method in class com.imsl.io.AbstractFlatFile: Sets a column name.
setColumnParser(int, FlatFile.Parser) - Method in class com.imsl.io.FlatFile: Sets the Parser for the specified column.
setColumnSpacing(int) - Method in class com.imsl.math.PrintMatrix: Sets the number of spaces between columns.
setComponent(Component) - Method in class com.imsl.chart.Chart: Sets the Component for this chart.
setConLevelMean(double) - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Sets the confidence level for two-sided interval estimates on the mean, in percent.
setConLevelPred(double) - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Sets the confidence level for two-sided prediction intervals, in percent.
setConfidence(double) - Method in class com.imsl.stat.ARMA: Sets the confidence percent probability limits of the forecasts.
setConfidenceMean(double) - Method in class com.imsl.stat.NormOneSample: Sets the confidence level (in percent) for a two-sided interval estimate of the mean.
setConfidenceMean(double) - Method in class com.imsl.stat.NormTwoSample: Sets the confidence level (in percent) for a two-sided interval estimate of the mean of x - the mean of y, in percent.
setConfidenceVariance(double) - Method in class com.imsl.stat.NormOneSample: Sets the confidence level (in percent) for two-sided interval estimate of the variances.
setConfidenceVariance(double) - Method in class com.imsl.stat.NormTwoSample: Sets the confidence level (in percent) for two-sided interval estimate of the variances.
setConstraintType(int[]) - Method in class com.imsl.math.DenseLP: Sets the types of general constraints in the matrix a.
setConstraintType(int[]) - Method in class com.imsl.math.LinearProgramming: Sets the types of general constraints in the matrix a.
setConvergenceCriterion1(double) - Method in class com.imsl.stat.FactorAnalysis: Sets the convergence criterion used to terminate the iterations.
setConvergenceCriterion2(double) - Method in class com.imsl.stat.FactorAnalysis: Sets the convergence criterion used to switch to exact second derivatives.
setConvergenceTolerance(double) - Method in class com.imsl.stat.ARMA: Sets the tolerance level used to determine convergence of the nonlinear least-squares algorithm.
setConvergenceTolerance(double) - Method in class com.imsl.stat.CategoricalGenLinModel: Set the convergence criterion.
setCoordinates(double[][]) - Method in class com.imsl.chart.Dendrogram: Convenience routine to set the "Coordinates" attribute.
setCovarianceComputation(int) - Method in class com.imsl.stat.DiscriminantAnalysis: Sets the type of covariance matrices to be computed.
setCreateImageMap(boolean) - Method in class com.imsl.chart.JspBean: Sets a flag indicating if a client-size imagemap is to be generated.
setCriterionOption(int) - Method in class com.imsl.stat.SelectionRegression: Sets the Criterion to be used.
setCross(double, double) - Method in class com.imsl.chart.AxisXY: Sets the value of the "Cross" attribute.
setCross(double[]) - Method in class com.imsl.chart.AxisXY: Sets the value of the "Cross" attribute.
setCustomMarker(Data.CustomMarkerFactory) - Method in class com.imsl.chart3d.Data: Sets a custom marker factory.
setCustomTransform(Transform) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "CustomTransform" attribute.
setCustomTransform(Transform) - Method in class com.imsl.chart.ChartNode: Sets the value of the "CustomTransform" attribute.
setCutpoints(double[]) - Method in class com.imsl.stat.ChiSquaredTest: Sets the cutpoints.
setData(double[]) - Method in class com.imsl.chart.Pie: Changes the data in a Pie chart object.
setDataType(int) - Method in class com.imsl.chart.ChartNode: Sets the value of the "DataType" attribute.
setDataType(int) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "DataType" attribute.
setDateAxis(String) - Method in class com.imsl.chart.HighLowClose: Sets up the x-axis for high-low-close plot.
setDateColumnParser(int, String, Locale) - Method in class com.imsl.io.FlatFile: Creates for a pattern string and sets the Parser for the specified column.
setDefaultAlignment(int) - Method in class com.imsl.chart.Text: Sets the alignment to use, if it has not been set using setAlignment(int).
setDefaultOffset(double) - Method in class com.imsl.chart.Text: Sets the default value of the offset.
setDegreesOfFreedom(int) - Method in class com.imsl.stat.FactorAnalysis: Sets the number of degrees of freedom.
setDensity(int) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "Density" attribute.
setDerivtol(double) - Method in class com.imsl.math.MinUncon: Set the derivative tolerance used by member function computeMin to decide if the current point is a local minimum.
setDiagonalScalingMatrix(double[]) - Method in class com.imsl.math.BoundedLeastSquares: Sets the diagonal scaling matrix for the functions.
setDifferentiationType(int) - Method in class com.imsl.math.MinConNLP: Set the type of numerical differentiation to be used.
setDigits(double) - Method in class com.imsl.math.MinUnconMultiVar: Set the number of good digits in the function.
setDigits(int) - Method in class com.imsl.math.NonlinLeastSquares: Set the number of good digits in the function.
setDigits(int) - Method in class com.imsl.stat.NonlinearRegression: Sets the number of good digits in the residuals.
setDirection(double, double, double) - Method in class com.imsl.chart3d.DirectionalLight: Sets the value of the "Direction" attribute to a light direction.
setDirection(Vector3f) - Method in class com.imsl.chart3d.DirectionalLight: Sets the value of the "Direction" attribute to a light direction.
setDiscriminationMethod(int) - Method in class com.imsl.stat.DiscriminantAnalysis: Sets the discrimination method.
setDoubleBuffering(boolean) - Method in class com.imsl.chart.ChartNode: Sets the value of the "DoubleBuffering" attribute.
setEffects(int[], int[]) - Method in class com.imsl.stat.CategoricalGenLinModel: Initializes an index vector to contain the column numbers in x associated with each effect.
setEffects(int) - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Sets the effect option.
setEpochNumber(int) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Sets the epoch number for the trainer.
setEpochNumber(int) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Sets the epoch number for the trainer.
setEpochSize(int) - Method in class com.imsl.datamining.neural.EpochTrainer: Sets the number of randomly selected training patterns in stage 1 epoch.
setEqualColumnWidths(boolean) - Method in class com.imsl.math.PrintMatrix: Force all of the columns to have the same width.
setEqualWeights(double[][]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Initializes network weights using equal weighting.
setError(QuasiNewtonTrainer.Error) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Sets the function used to compute the network error.
setErrorIncludeType(int) - Method in class com.imsl.stat.ANOVAFactorial: Sets error included type.
setExplode(double) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Explode" attribute.
setExtendedLikelihoodObservations(int[]) - Method in class com.imsl.stat.CategoricalGenLinModel: Initializes a vector indicating which observations are to be included in the extended likelihood.
setExtrapolation(boolean) - Method in class com.imsl.math.Quadrature: If true, the epsilon-algorithm for extrapolation is enabled.
setFactorLoadingEstimationMethod(int) - Method in class com.imsl.stat.FactorAnalysis: Sets the factor loading estimation method.
setFalseConvergenceTolerance(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Set the false convergence tolerance.
setFalseConvergenceTolerance(double) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Set the false convergence tolerance for the Trainer.
setFalseConvergenceTolerance(double) - Method in class com.imsl.math.MinUnconMultiVar: Set the false convergence tolerance.
setFalseConvergenceTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares: Set the false convergence tolerance.
setFalseConvergenceTolerance(double) - Method in class com.imsl.stat.NonlinearRegression: Sets the false convergence tolerance.
setFetchDirection(int) - Method in class com.imsl.io.AbstractFlatFile: Gives a hint as to the direction in which the rows in this ResultSet object will be processed.
setFetchSize(int) - Method in class com.imsl.io.AbstractFlatFile: Gives the JDBC driver a hint as to the number of rows that should be fetched from the database when more rows are needed for this ResultSet object.
setFillColor(Color) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "FillColor" attribute.
setFillColor(String) - Method in class com.imsl.chart.AbstractChartNode: Sets the "FillColor" attribute to a color specified by name.
setFillOutlineColor(Color) - Method in class com.imsl.chart.ChartNode: Sets the value of the "FillOutlineColor" attribute.
setFillOutlineColor(String) - Method in class com.imsl.chart.ChartNode: Sets the value of the "FillOutlineColor" attribute to a color specified by name.
setFillOutlineType(int) - Method in class com.imsl.chart.ChartNode: Sets the value of the "FillOutlineType" attribute.
setFillPaint(Paint) - Method in class com.imsl.chart.ChartNode: Sets the value of the "FillPaint" attribute.
setFillPaint(ImageIcon) - Method in class com.imsl.chart.ChartNode: Sets the value of the "FillPaint" attribute.
setFillPaint(URL) - Method in class com.imsl.chart.ChartNode: Sets the value of the "FillPaint" attribute.
setFillType(int) - Method in class com.imsl.chart.ChartNode: Sets the value of the "FillType" attribute.
setFirstColumnNumber(int) - Method in class com.imsl.math.PrintMatrixFormat: Turns on column labeling with index numbers and sets the index for the label of the first column.
setFirstRowNumber(int) - Method in class com.imsl.math.PrintMatrixFormat: Turns on row labeling with index numbers and sets the index for the label of the first row.
setFirstTick(double) - Method in class com.imsl.chart.Axis1D: Convenience routine to set the "FirstTick" attribute.
setFirstTick(double) - Method in class com.imsl.chart3d.Axis3D: Convenience routine to set the "FirstTick" attribute.
setFixedParameterColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the column number in x that contains a fixed parameter for each observation that is added to the linear response prior to computing the model parameter.
setFloor(double) - Method in class com.imsl.math.OdeRungeKutta: Sets the value used in the norm computation.
setFont(Font) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the font attributes.
setFontName(String) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "FontName" attribute.
setFontSize(int) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "FontSize" attribute.
setFontStyle(int) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "FontStyle" attribute.
setForce(int) - Method in class com.imsl.stat.StepwiseRegression: Forces independent variables into the model based on their level assigned from setlevels.
setFrequencies(double[]) - Method in class com.imsl.stat.ClusterKMeans: Sets the frequency for each observation.
setFrequencies(double[]) - Method in class com.imsl.stat.Covariances: Sets the frequency for each observation.
setFrequencies(double[]) - Method in class com.imsl.stat.TableMultiWay
setFrequency(int[]) - Static method in class com.imsl.stat.KaplanMeierECDF: Sets the frequency for each entry in y
setFrequencyColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the column number in x that contains the frequency of response for each observation.
setFscale(double) - Method in class com.imsl.math.MinUnconMultiVar: Set the function scaling value for scaling the gradient.
setFscale(double[]) - Method in class com.imsl.math.NonlinLeastSquares: Set the diagonal scaling matrix for the functions.
setFunctionPrecision(double) - Method in class com.imsl.math.MinConNLP: Set the relative precision of the function evaluation routine.
setFuzz(double) - Method in class com.imsl.stat.Ranks: Sets the fuzz factor used in determining ties.
setFuzz(double) - Method in class com.imsl.stat.WilcoxonRankSum: Sets the nonnegative constant used to determine ties in computing ranks in the combined samples.
setGoodDigit(int) - Method in class com.imsl.math.BoundedLeastSquares: Sets the number of good digits in the function.
setGradient(Color, Color, Color, Color) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Gradient" attribute.
setGradient(String, String, String, String) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Gradient" attribute using named colors.
setGradient(Color[]) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Gradient" attribute.
setGradientPrecision(double) - Method in class com.imsl.math.MinConNLP: Set the relative precision in gradients.
setGradientTol(double) - Method in class com.imsl.math.BoundedLeastSquares: Sets the scaled gradient tolerance.
setGradientTolerance(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Set the gradient tolerance.
setGradientTolerance(double) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Set the gradient tolerance.
setGradientTolerance(double) - Method in class com.imsl.math.MinUnconMultiVar: Sets the gradient tolerance.
setGradientTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares: Set the gradient tolerance used to compute the gradient.
setGradientTolerance(double) - Method in class com.imsl.stat.NonlinearRegression: Sets the gradient tolerance used to compute the gradient.
setGuess(double[]) - Method in class com.imsl.math.BoundedLeastSquares: Sets the initial guess of the solution.
setGuess(double[]) - Method in class com.imsl.math.MinConGenLin: Sets an initial guess of the solution.
setGuess(double[]) - Method in class com.imsl.math.MinConNLP: Set the initial guess of the minimum point of the input function.
setGuess(double) - Method in class com.imsl.math.MinUncon: Set the initial guess of the minimum point of the input function.
setGuess(double[]) - Method in class com.imsl.math.MinUnconMultiVar: Set the initial guess of the minimum point of the input function.
setGuess(double[]) - Method in class com.imsl.math.NonlinLeastSquares: Set the initial guess of the minimum point of the input function.
setGuess(double[]) - Method in class com.imsl.math.ZeroSystem: Sets the initial guess for the array x.
setGuess(double[]) - Method in class com.imsl.stat.NonlinearRegression: Sets the initial guess of the parameter values
setHREF(String) - Method in class com.imsl.chart.ChartNode: Sets the value of the "HREF" attribute.
setHeatmapLabels(String[][]) - Method in class com.imsl.chart.Heatmap: Sets the value of the "HeatmapLabels" attribute.
setHeatmapLabels(Text[][]) - Method in class com.imsl.chart.Heatmap: Sets the value of the "HeatmapLabels" attribute.
setHigh(double[]) - Method in class com.imsl.chart.ErrorBar: Convenience routine to set the "High" attribute.
setHigh(double[]) - Method in class com.imsl.chart.HighLowClose: Convenience routine to set the "High" attribute.
setIhess(int) - Method in class com.imsl.math.MinUnconMultiVar: Set the Hessian initialization parameter.
setImage(ImageIcon) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "Image" attribute.
setImage(Image) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Image" attribute.
setInfiniteEstimateMethod(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the method to be used for handling infinite estimates.
setInitialEstimates(double[], double[]) - Method in class com.imsl.stat.ARMA: Sets preliminary estimates.
setInitialEstimates(int, double[]) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the initial parameter estimates option.
setInitialStepsize(double) - Method in class com.imsl.math.OdeRungeKutta: Sets the initial internal step size.
setInitialTrustRegion(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Sets the intial trust region.
setInitialTrustRegion(double) - Method in class com.imsl.math.NonlinLeastSquares: Set the initial trust region radius.
setInitialTrustRegion(double) - Method in class com.imsl.stat.NonlinearRegression: Sets the initial trust region radius.
setInternalScale() - Method in class com.imsl.math.BoundedLeastSquares: Sets the internal variable scaling option.
setJacobian(BoundedLeastSquares.Jacobian) - Method in class com.imsl.math.BoundedLeastSquares: Sets the Jacobian.
setKeyboard(boolean) - Method in class com.imsl.chart3d.Chart3D: Sets the value of the "Keyboard" attribute.
setLabelType(int) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "LabelType" attribute.
setLabels(String[]) - Method in class com.imsl.chart.AxisLabel: Sets the axis label values for this node to be used instead of the default numbers.
setLabels(String[]) - Method in class com.imsl.chart.AxisRLabel: Sets the axis label values for this node to be used instead of the default numbers.
setLabels(String[], int) - Method in class com.imsl.chart.Bar: Sets up an axis with bar labels.
setLabels(String[]) - Method in class com.imsl.chart.Bar: Sets up an axis with bar labels.
setLabels(String[], int) - Method in class com.imsl.chart.BoxPlot: Sets up an axis with labels.
setLabels(String[]) - Method in class com.imsl.chart.BoxPlot: Sets up an axis with labels.
setLabels(String[]) - Method in class com.imsl.chart.Dendrogram: Sets up the axis labels for dendrogram plot.
setLabels(String[]) - Method in class com.imsl.chart3d.AxisLabel: Sets the axis label values for this node to be used instead of the default numbers.
setLeftSons(int[]) - Method in class com.imsl.chart.Dendrogram: Convenience routine to set the "LeftSons" attribute.
setLevels(double[]) - Method in class com.imsl.chart.Dendrogram: Convenience routine to set the "Levels" attribute.
setLevels(int[]) - Method in class com.imsl.stat.StepwiseRegression: Sets the levels of priority for variables entering and leaving the regression.
setLightColor(Color) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "LightColor" attribute.
setLightColor(String) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "LightColor" attribute to a color specified by name.
setLineColor(Color) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "LineColor" attribute.
setLineColor(String) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "LineColor" attribute.
setLineColor(String[]) - Method in class com.imsl.chart.Dendrogram: Define colors for individual clusters.
setLineColor(Color[]) - Method in class com.imsl.chart.Dendrogram: Define colors for individual clusters.
setLineDashPattern(double[]) - Method in class com.imsl.chart.ChartNode: Sets the value of the "LineDashPattern" attribute.
setLineWidth(double) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "LineWidth" attribute.
setLocale(Locale) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "Locale" attribute.
setLow(double[]) - Method in class com.imsl.chart.ErrorBar: Convenience routine to set the "Low" attribute.
setLow(double[]) - Method in class com.imsl.chart.HighLowClose: Convenience routine to set the "Low" attribute.
setLowerBound(double[]) - Method in class com.imsl.math.DenseLP: Sets the lower bound, , on the variables.
setLowerBound(double[]) - Method in class com.imsl.math.LinearProgramming: Sets the lower bound on the variables.
setLowerEndpointColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the column number in x that contains the lower endpoint of the observation interval for full interval and right interval observations.
setMALags(int[]) - Method in class com.imsl.stat.ARMA: Sets the order of the moving average parameters.
setMarkerColor(Color) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "MarkerColor" attribute.
setMarkerColor(String) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "MarkerColor" attribute to a color specified by name.
setMarkerDashPattern(double[]) - Method in class com.imsl.chart.ChartNode: Sets the value of the "MarkerDashPattern" attribute.
setMarkerPulsingCycle(double) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "MarkerPulsingCycle" attribute.
setMarkerPulsingCycleOffset(double) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "MarkerPulsingCycleOffset" attribute.
setMarkerPulsingMaximumScale(double) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "MarkerPulsingMaximumScale" attribute.
setMarkerPulsingMinimumScale(double) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "MarkerPulsingMinimumScale" attribute.
setMarkerRotatingAxis(double, double, double) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "MarkerRotatingAxis" attribute.
setMarkerRotatingCycle(double) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "MarkerRotatingCycle" attribute.
setMarkerRotatingCycleOffset(double) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "MarkerRotatingCycleOffset" attribute.
setMarkerSize(double) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "MarkerSize" attribute.
setMarkerThickness(double) - Method in class com.imsl.chart.ChartNode: Sets the value of the "MarkerThickness" attribute.
setMarkerType(int) - Method in class com.imsl.chart.ChartNode: Sets the value of the "MarkerType" attribute.
setMarkerType(int) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "MarkerType" attribute.
setMaterial(Material) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "Material" attribute.
setMatrixType(int) - Method in class com.imsl.math.PrintMatrix: Set matrix type.
setMaxIterations(int) - Method in class com.imsl.math.MinConNLP: Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.MinUnconMultiVar: Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.NonlinLeastSquares: Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.ZeroFunction: Sets the maximum number of iterations allowed per root.
setMaxIterations(int) - Method in class com.imsl.math.ZeroPolynomial: Sets the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.ZeroSystem: Sets the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.stat.ARMA: Sets the maximum number of iterations.
setMaxIterations(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.stat.ClusterKMeans: Sets the maximum number of iterations.
setMaxIterations(int) - Method in class com.imsl.stat.FactorAnalysis: Sets the maximum number of iterations in the iterative procedure.
setMaxIterations(int) - Method in class com.imsl.stat.NonlinearRegression: Sets the maximum number of iterations allowed during optimization
setMaxSigma(double) - Method in class com.imsl.stat.GARCH: Sets the value of the upperbound on the first element (sigma) of the array of returned estimated coefficients.
setMaxStep(int) - Method in class com.imsl.stat.FactorAnalysis: Sets the maximum number of step halvings allowed during an iteration.
setMaxSteps(int) - Method in class com.imsl.math.OdeRungeKutta: Sets the maximum number of internal steps allowed.
setMaxStepsize(double) - Method in class com.imsl.stat.NonlinearRegression: Sets the maximum allowable stepsize.
setMaxSubintervals(int) - Method in class com.imsl.math.Quadrature: Sets the maximum number of subintervals allowed.
setMaximumBestFound(int) - Method in class com.imsl.stat.SelectionRegression: Sets the maximum number of best regressions to be found.
setMaximumFunctionEvals(int) - Method in class com.imsl.math.BoundedLeastSquares: Sets the maximum number of function evaluations.
setMaximumGoodSaved(int) - Method in class com.imsl.stat.SelectionRegression: Sets the maximum number of good regressions for each subset size saved.
setMaximumIteration(int) - Method in class com.imsl.math.BoundedLeastSquares: Sets the maximum number of iterations.
setMaximumIteration(int) - Method in class com.imsl.math.LinearProgramming: Sets the maximum number of iterations.
setMaximumJacobianEvals(int) - Method in class com.imsl.math.BoundedLeastSquares: Sets the maximum number of Jacobian evaluations.
setMaximumStepSize(double) - Method in class com.imsl.math.BoundedLeastSquares: Sets the maximum allowable step size.
setMaximumStepsize(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Sets the maximum step size.
setMaximumStepsize(double) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Sets the maximum step size.
setMaximumStepsize(double) - Method in class com.imsl.math.MinUnconMultiVar: Set the maximum allowable stepsize to use.
setMaximumStepsize(double) - Method in class com.imsl.math.NonlinLeastSquares: Set the maximum allowable stepsize to use.
setMaximumStepsize(double) - Method in class com.imsl.math.OdeRungeKutta: Sets the maximum internal step size.
setMaximumSubsetSize(int) - Method in class com.imsl.stat.SelectionRegression: Sets the maximum subset size if criterion is used.
setMaximumTime(long) - Method in class com.imsl.math.MinConNLP: Sets the maximum time allowed for the solve step.
setMaximumTrainingIterations(int) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Sets the maximum number of iterations used by the nonlinear least squares solver.
setMaximumTrainingIterations(int) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Sets the maximum number of iterations to use in a training.
setMean(double) - Method in class com.imsl.stat.AutoCorrelation: Estimate mean of the time series x.
setMeanEstimate(double) - Method in class com.imsl.stat.ARMA: Sets an initial estimate of the mean of the time series z.
setMeanX(double) - Method in class com.imsl.stat.CrossCorrelation: Estimate of the mean of time series x.
setMeanX(double[]) - Method in class com.imsl.stat.MultiCrossCorrelation: Estimate of the mean of each channel of x.
setMeanY(double) - Method in class com.imsl.stat.CrossCorrelation: Estimate of the mean of time series y.
setMeanY(double[]) - Method in class com.imsl.stat.MultiCrossCorrelation: Estimate of the mean of each channel of y.
setMethod(int) - Method in class com.imsl.stat.ARMA: Sets the method to be used by the class.
setMethod(int) - Method in class com.imsl.stat.StepwiseRegression: Specifies the stepwise selection method, forward, backward, or stepwise Regression.
setMinimumStepsize(double) - Method in class com.imsl.math.OdeRungeKutta: Sets the minimum internal step size.
setMissingValueMethod(int) - Method in class com.imsl.stat.Covariances: Sets the method used to exclude missing values in x from the computations, where Double.NaN is interpreted as the missing value code.
setModelIntercept(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the intercept option.
setModelOrder(int) - Method in class com.imsl.stat.ANOVAFactorial: Sets the number of factors to be included in the highest-way interaction in the model.
setMultiplier(int) - Method in class com.imsl.stat.Random: Sets the multiplier for a linear congruential random number generator.
setMultiplierError(double) - Method in class com.imsl.math.MinConNLP: Set the error allowed in the multipliers.
setName(String) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "Name" attribute.
setNameBounds(String) - Method in class com.imsl.io.MPSReader: Sets the name of the BOUNDS set to be used.
setNameObjective(String) - Method in class com.imsl.io.MPSReader: Sets the name of the free row containing the objective.
setNameRHS(String) - Method in class com.imsl.io.MPSReader: Sets the name of the RHS set to be used.
setNameRanges(String) - Method in class com.imsl.io.MPSReader: Sets the name of the RANGES set to be used.
setNoColumnLabels() - Method in class com.imsl.math.PrintMatrixFormat: Turns off column labels.
setNoRowLabels() - Method in class com.imsl.math.PrintMatrixFormat: Turns off row labels.
setNode(ChartNode) - Method in class com.imsl.chart.Draw: Set the current ChartNode.
setNode(ChartNode) - Method in class com.imsl.chart.DrawMap: Set the current ChartNode.
setNode(ChartNode) - Method in class com.imsl.chart.DrawPick: Set the current ChartNode.
setNode(ChartNode) - Method in class com.imsl.chart.PickEvent: Sets the ChartNode.
setNorm(int) - Method in class com.imsl.math.OdeRungeKutta: Sets the switch for determining the error norm.
setNotch(boolean) - Method in class com.imsl.chart.BoxPlot: Sets the attribute "Notch".
setNumber(int) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "Number" attribute.
setNumberFormat(NumberFormat) - Method in class com.imsl.math.PrintMatrixFormat: Sets the NumberFormat to be used in formatting double and Complex entries.
setNumberGridPointsX(int) - Method in class com.imsl.chart3d.Surface: Sets the value of the "NumberGridPointsX" attribute.
setNumberGridPointsY(int) - Method in class com.imsl.chart3d.Surface: Sets the value of the "NumberGridPointsY" attribute.
setNumberOfEpochs(int) - Method in class com.imsl.datamining.neural.EpochTrainer: Sets the number of epochs.
setNumberOfThreads(int) - Method in class com.imsl.datamining.neural.EpochTrainer: Sets the number of threads to use during stage I training.
setObservationMax(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the maximum number of observations that can be handled in the linear programming.
setOffset(double) - Method in class com.imsl.chart.Text: Sets the offset.
setOpen(double[]) - Method in class com.imsl.chart.HighLowClose: Sets the attribute "Open".
setOptionalDistributionParameterColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the column number in x that contains an optional distribution parameter for each observation.
setOrbit(boolean) - Method in class com.imsl.chart3d.Chart3D: Sets the value of the "Orbit" attribute.
setOrder(int[]) - Method in class com.imsl.chart.Dendrogram: Convenience routine to set the "Order" attribute.
setOrders(int[]) - Method in class com.imsl.stat.Difference: Sets the orders for the Difference object
setOut(PrintStream) - Static method in class com.imsl.Warning: Reassigns the output stream.
setOut(PrintStream) - Method in class com.imsl.WarningObject: Reassigns the output stream.
setPValueIn(double) - Method in class com.imsl.stat.StepwiseRegression: Defines the largest p-value for variables entering the model.
setPValueOut(double) - Method in class com.imsl.stat.StepwiseRegression: Defines the smallest p-value for removing variables.
setPageWidth(int) - Method in class com.imsl.math.PrintMatrix: Sets the page width.
setPaint(boolean) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "Paint" attribute.
setParallelMode(ArrayList[]) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Sets the trainer to be used in multi-threaded EpochTainer.
setParallelMode(ArrayList[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Sets the trainer to be used in multi-threaded EpochTainer.
setPenaltyBound(double) - Method in class com.imsl.math.MinConNLP: Set the universal bound for describing how much the unscaled penalty-term may deviate from zero.
setPercentage(double) - Method in class com.imsl.stat.SignTest: Sets the percentage percentile of the population.
setPercentages(double[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Set the untransformed cumulative percentages used during encoding and decoding.
setPercentile(double) - Method in class com.imsl.stat.SignTest: Sets the hypothesized percentile of the population.
setPosition(int, int) - Method in class com.imsl.chart3d.ColormapLegend: Sets the position of the legend.
setPosition(double, double, double) - Method in class com.imsl.chart3d.PointLight: Sets the value of the "Point" attribute to a light point.
setPosition(Point3f) - Method in class com.imsl.chart3d.PointLight: Sets the value of the "Point" attribute to a light point.
setPrior(int) - Method in class com.imsl.stat.DiscriminantAnalysis: Sets the type of prior probabilities to be computed.
setPrior(double[]) - Method in class com.imsl.stat.DiscriminantAnalysis: Sets the prior probabilities.
setProportionalWidth(boolean) - Method in class com.imsl.chart.BoxPlot: Sets the value of the attribute "ProportionalWidth".
setQ(double[][]) - Method in class com.imsl.stat.KalmanFilter: Sets the Q matrix.
setRadialFunction(RadialBasis.Function) - Method in class com.imsl.math.RadialBasis: Sets the radial function.
setRandom(Random) - Method in class com.imsl.datamining.neural.EpochTrainer: Sets the random number generator used to perturb the initial stage 1 guesses.
setRandom(Random) - Method in class com.imsl.stat.Ranks: Sets the Random object.
setRandomSamples(Random, Random) - Method in class com.imsl.datamining.neural.EpochTrainer: Sets the random number generators used to select random training patterns in stage 1.
setRandomWeights(double[][], Random) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Initializes network weights using random weights.
setRange(double, double) - Method in class com.imsl.stat.ChiSquaredTest: Sets endpoints of the range of the distribution.
setReference(double) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Reference" attribute.
setRefinementType(int) - Method in class com.imsl.math.DenseLP: Set the type of refinement used.
setRelativeError(double) - Method in class com.imsl.math.HyperRectangleQuadrature: Sets the relative error tolerance.
setRelativeError(double) - Method in class com.imsl.math.Quadrature: Sets the relative error tolerance.
setRelativeError(double) - Method in class com.imsl.math.ZeroFunction: Sets second stopping criterion is the relative error.
setRelativeError(double) - Method in class com.imsl.math.ZeroSystem: Sets the relative error tolerance.
setRelativeError(double) - Method in class com.imsl.stat.ARMA: Sets the stopping criterion for use in the nonlinear equation solver.
setRelativeFcnTol(double) - Method in class com.imsl.math.BoundedLeastSquares: Sets the relative function tolerance.
setRelativeTolerance(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Sets the relative tolerance.
setRelativeTolerance(double) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Sets the relative tolerence.
setRelativeTolerance(double) - Method in class com.imsl.math.MinUnconMultiVar: Set the relative function tolerance.
setRelativeTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares: Set the relative function tolerance.
setRelativeTolerance(double) - Method in class com.imsl.stat.NonlinearRegression: Sets the relative function tolerance
setRightSons(int[]) - Method in class com.imsl.chart.Dendrogram: Convenience routine to set the "RightSons" attribute.
setRule(int) - Method in class com.imsl.math.Quadrature: Set the Gauss-Kronrod rule.
setScale(double) - Method in class com.imsl.math.OdeRungeKutta: Sets the scaling factor.
setScale(double[]) - Method in class com.imsl.stat.NonlinearRegression: Sets the scaling array for theta.
setScaleFont(double) - Method in class com.imsl.chart.Draw: Set a factor by which fonts are to be scaled.
setScaledStepTol(double) - Method in class com.imsl.math.BoundedLeastSquares: Sets the scaled step tolerance.
setScalingBound(double) - Method in class com.imsl.math.MinConNLP: Set the scaling bound for the internal automatic scaling of the objective function.
setScalingVector(double[]) - Method in class com.imsl.math.BoundedLeastSquares: Sets the scaling vector for the variables.
setScreenSize(Dimension) - Method in class com.imsl.chart.ChartNode: Sets the value of the "ScreenSize" attribute.
setSeed(long) - Method in class com.imsl.stat.Random: Sets the seed.
setSize(Dimension) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Size" attribute.
setSize(Dimension) - Method in class com.imsl.chart.JspBean: Sets the size of the generated image.
setSize(int, int) - Method in class com.imsl.chart.JspBean: Sets the size of the generated image.
setSkipWeekends(boolean) - Method in class com.imsl.chart.ChartNode: Sets the value of the "SkipWeekends" attribute.
setSpread(double) - Method in class com.imsl.datamining.neural.ScaleFilter: Set the measure of spread to be used during z-score scaling.
setSpread(double) - Method in class com.imsl.math.ZeroFunction: Sets the spread.
setSpreadTolerance(double) - Method in class com.imsl.math.ZeroFunction: Sets the spread criteria for multiple zeros.
setStep(double) - Method in class com.imsl.math.MinUncon: Set the stepsize to use when changing x.
setStepTolerance(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Set the step tolerance used to step between weights.
setStepTolerance(double) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Sets the scaled step tolerance.
setStepTolerance(double) - Method in class com.imsl.math.MinUnconMultiVar: Set the scaled step tolerance to use when changing x.
setStepTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares: Set the step tolerance used to step between two points.
setStepTolerance(double) - Method in class com.imsl.stat.NonlinearRegression: Sets the step tolerance used to step between two points.
setString(String) - Method in class com.imsl.chart.Text: Sets the string for this Text object.
setSurfaceType(int) - Method in class com.imsl.chart3d.Surface: Sets the attribute "SurfaceType".
setTTestNull(double) - Method in class com.imsl.stat.NormOneSample: Sets the Null hypothesis value for t test for the mean.
setTTestNull(double) - Method in class com.imsl.stat.NormTwoSample: Sets the Null hypothesis value for t-test for the mean.
setTextAngle(int) - Method in class com.imsl.chart.ChartNode: Sets the value of the "TextAngle" attribute.
setTextColor(Color) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "TextColor" attribute.
setTextColor(String) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "TextColor" attribute to a color specified by name.
setTextColor(Color) - Method in class com.imsl.chart.ChartNode: Sets the value of the "TextColor" attribute.
setTextColor(String) - Method in class com.imsl.chart.ChartNode: Sets the value of the "TextColor" attribute to a color specified by name.
setTextFormat(Format) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "TextFormat" attribute.
setTextFormat(String) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "TextFormat" attribute.
setTickInterval(double) - Method in class com.imsl.chart.Axis1D: Sets the tick interval.
setTickInterval(double) - Method in class com.imsl.chart.AxisR: Sets the tick interval.
setTickInterval(double) - Method in class com.imsl.chart3d.Axis3D: Sets the tick interval.
setTickLength(double) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "TickLength" attribute.
setTicks(double[]) - Method in class com.imsl.chart.Axis1D: Sets the value of the "Ticks" attribute.
setTicks(double[]) - Method in class com.imsl.chart3d.Axis3D: Sets the value of the "Ticks" attribute.
setTicks(double[]) - Method in class com.imsl.chart3d.ColormapLegend: Sets the value of the "Ticks" attribute.
setTieBreaker(int) - Method in class com.imsl.stat.Ranks: Sets the tie breaker for Ranks.
setTitle(String) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Title" attribute.
setTitle(Text) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Title" attribute.
setTitle(String) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "Title" attribute.
setTitle(String) - Method in class com.imsl.math.PrintMatrix: Sets matrix title
setTolerance(int) - Method in class com.imsl.chart.DrawMap: Set the minimum distance that an event can be from a point or a line and still be considered a hit.
setTolerance(int) - Method in class com.imsl.chart.DrawPick: Set the minimum distance that an event can be from a point or a line and still be considered a hit.
setTolerance(double) - Method in class com.imsl.math.MinConGenLin: Sets the nonnegative tolerance on the first order conditions at the calculated solution.
setTolerance(double) - Method in class com.imsl.math.MinConNLP: Set the desired precision of the solution.
setTolerance(double) - Method in class com.imsl.math.OdeRungeKutta: Sets the error tolerance.
setTolerance(double) - Method in class com.imsl.stat.InverseCdf: Sets the tolerance to be used as the convergence criterion.
setTolerance(double) - Method in class com.imsl.stat.KalmanFilter: Sets the tolerance used in determining linear dependence.
setTolerance(double) - Method in class com.imsl.stat.StepwiseRegression: The tolerance used to detect linear dependence among the independent variables.
setToolTip(String) - Method in class com.imsl.chart.ChartNode: Sets the value of the "ToolTip" attribute.
setTransform(int) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "Transform" attribute.
setTransitionMatrix(double[][]) - Method in class com.imsl.stat.KalmanFilter: Sets the transition matrix.
setTrustRegion(double) - Method in class com.imsl.math.BoundedLeastSquares: Sets the size of initial trust region radius.
setType(int) - Method in class com.imsl.chart.Axis1D: Sets the type of this node.
setUnequalVariances(boolean) - Method in class com.imsl.stat.NormTwoSample: Specifies whether to return statistics based on equal or unequal variances.
setUpperBound(double[]) - Method in class com.imsl.math.DenseLP: Sets the upper bound, , on the variables.
setUpperBound(double[]) - Method in class com.imsl.math.LinearProgramming: Sets the upper bound on the variables.
setUpperBound(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the upper bound on the sum of the number of distinct values taken on by each classification variable.
setUpperEndpointColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel: Sets the column number in x that contains the upper endpoint of the observation interval for full interval and left interval observations.
setUpperLimit(double[]) - Method in class com.imsl.math.DenseLP: Sets the upper limit of the constraints.
setUpperLimit(double[]) - Method in class com.imsl.math.LinearProgramming: Sets the upper limit of the constraints.
setUseBackPropagation(boolean) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Sets whether or not to use the back propagation algorithm for gradient calculations during network training.
setValue(double) - Method in class com.imsl.datamining.neural.InputNode: Sets the value of this Node.
setVarianceEstimationMethod(int) - Method in class com.imsl.stat.FactorAnalysis: Sets the variance estimation method.
setVariances(double[]) - Method in class com.imsl.stat.FactorAnalysis: Sets the variances.
setViewPlatformTransformation(Transform3D) - Method in class com.imsl.chart3d.Chart3D: Sets the transformation for the view platform.
setViewport(double[]) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Viewport" attribute.
setViewport(double, double, double, double) - Method in class com.imsl.chart.ChartNode: Sets the value of the "Viewport" attribute.
setViewport(double[]) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "Viewport" attribute.
setViewport(double, double, double, double, double, double) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "Viewport" attribute.
setViolationBound(double) - Method in class com.imsl.math.MinConNLP: Set the scalar which defines allowable constraint violations of the final accepted result.
setVisibleFaces(int) - Method in class com.imsl.chart3d.AxisBox: Sets the "VisibleFaces" attribute indicating which faces of the box are to be drawn.
setWarning(WarningObject) - Static method in class com.imsl.Warning: Sets a new WarningObject.
setWarning(SQLWarning) - Method in class com.imsl.io.AbstractFlatFile: Sets a SQLWarning.
setWeight(double) - Method in class com.imsl.datamining.neural.Link: Sets the weight for this Link.
setWeights(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Sets the weights for the Links in this Network.
setWeights(double[]) - Method in class com.imsl.datamining.neural.Network: Sets the weights.
setWeights(double[]) - Method in class com.imsl.stat.ClusterKMeans: Sets the weight for each observation.
setWeights(double[]) - Method in class com.imsl.stat.Covariances: Sets the weight for each observation.
setWindow(double, double) - Method in class com.imsl.chart.Axis1D: Sets the window for an Axis1D.
setWindow(double[]) - Method in class com.imsl.chart.Axis1D: Sets the window for an Axis1D.
setWindow(double) - Method in class com.imsl.chart.AxisR: Sets the Window attribute.
setWindow(double, double) - Method in class com.imsl.chart.AxisTheta: Sets the window for an AxisTheta.
setWindow(double[]) - Method in class com.imsl.chart.AxisTheta: Sets the window for an AxisTheta.
setWindow(double[]) - Method in class com.imsl.chart.AxisXY: Sets the window in user coordinates along an axis.
setWindow(double, double) - Method in class com.imsl.chart3d.Axis3D: Sets the window for an Axis1D.
setWindow(double[]) - Method in class com.imsl.chart3d.Axis3D: Sets the window for an Axis1D.
setWindow(double, double) - Method in class com.imsl.chart3d.ColormapLegend: Sets the window for a ColormapLegend.
setWindow(double[]) - Method in class com.imsl.chart3d.ColormapLegend: Sets the window for a ColormapLegend.
setX(Object) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "X" attribute.
setXlowerBound(double[]) - Method in class com.imsl.math.MinConNLP: Set the lower bounds on the variables.
setXscale(double[]) - Method in class com.imsl.math.MinConNLP: Set the internal scaling of the variables.
setXscale(double[]) - Method in class com.imsl.math.MinUnconMultiVar: Set the diagonal scaling matrix for the variables.
setXscale(double[]) - Method in class com.imsl.math.NonlinLeastSquares: Set the diagonal scaling matrix for the variables.
setXupperBound(double[]) - Method in class com.imsl.math.MinConNLP: Set the upper bounds on the variables.
setY(Object) - Method in class com.imsl.chart.AbstractChartNode: Sets the value of the "Y" attribute.
setZ(Object) - Method in class com.imsl.chart3d.ChartNode3D: Sets the value of the "Z" attribute.
setupMapping() - Method in class com.imsl.chart.Axis: Initializes the mappings between user and coordinate space.
setupMapping() - Method in class com.imsl.chart.AxisXY: Initializes the mappings between user and coordinate space.
setupMapping() - Method in class com.imsl.chart.Pie: Initializes the mappings between user and coordinate space.
setupMapping() - Method in class com.imsl.chart.Polar: Initializes the mappings between user and coordinate space.
setupMapping(Axis1D) - Method in interface com.imsl.chart.Transform: Initializes the mappings between user and coordinate space.
setupMapping(Axis1D) - Method in class com.imsl.chart.TransformDate: Initializes the mappings between user and coordinate space.
shortValue() - Method in class com.imsl.math.Complex: Returns the value of the real part as a short.
sign(double, double) - Static method in class com.imsl.math.Sfun: Returns the value of x with the sign of y.
sin(Complex) - Static method in class com.imsl.math.Complex: Returns the sine of a Complex.
sin(double) - Static method in class com.imsl.math.JMath: Returns the sine of a double.
sinh(Complex) - Static method in class com.imsl.math.Complex: Returns the hyperbolic sine of a Complex.
sinh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the hyperbolic sine of its argument.
skewness(double[]) - Static method in class com.imsl.stat.Summary: Returns the skewness of the given data set.
skewness(double[], double[]) - Static method in class com.imsl.stat.Summary: Returns the skewness of the given data set and associated weights.
skip(int) - Method in class com.imsl.stat.Random: Resets the seed to skip ahead in the base linear congruential generator.
sln(double, double, int) - Static method in class com.imsl.finance.Finance: Returns the depreciation of an asset using the straight line method.
solve() - Method in class com.imsl.math.BoundedLeastSquares: Solves a nonlinear least-squares problem subject to bounds on the variables using a modified Levenberg-Marquardt algorithm.
solve(double[]) - Method in class com.imsl.math.Cholesky: Solve Ax = b where A is a positive definite matrix with elements of type double.
solve(Complex[]) - Method in class com.imsl.math.ComplexLU: Return the solution x of the linear system Ax = b using the LU factorization of A.
solve(Complex[][], Complex[]) - Static method in class com.imsl.math.ComplexLU: Solve ax=b for x using the LU factorization of a.
solve() - Method in class com.imsl.math.DenseLP: Solves the problem using an active set method.
solve(double[]) - Method in class com.imsl.math.LU: Return the solution x of the linear system Ax = b using the LU factorization of A.
solve(double[][], double[]) - Static method in class com.imsl.math.LU: Solve ax=b for x using the LU factorization of a.
solve() - Method in class com.imsl.math.LinearProgramming: Solves the program using the revised simplex algorithm.
solve() - Method in class com.imsl.math.MinConGenLin: Minimizes a general objective function subject to linear equality/inequality constraints.
solve(MinConNLP.Function) - Method in class com.imsl.math.MinConNLP: Solve a general nonlinear programming problem using the successive quadratic programming algorithm with a finite-difference gradient or with a user-supplied gradient.
solve(NonlinLeastSquares.Function) - Method in class com.imsl.math.NonlinLeastSquares: Solve a nonlinear least-squares problem using a modified Levenberg-Marquardt algorithm and a Jacobian.
solve(double, double, double[]) - Method in class com.imsl.math.OdeRungeKutta: Integrates the ODE system from x to xEnd.
solve(double[]) - Method in class com.imsl.math.QR: Returns the solution to the least-squares problem Ax = b.
solve(double[], double) - Method in class com.imsl.math.QR: Returns the solution to the least-squares problem Ax = b using an input tolerance.
solve(ZeroSystem.Function) - Method in class com.imsl.math.ZeroSystem: Solve a system of nonlinear equations using the Levenberg-Marquardt algorithm
solve() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the parameter estimates and associated statistics for a CategoricalGenLinModel object.
solve(NonlinearRegression.Function) - Method in class com.imsl.stat.NonlinearRegression: Solves the least squares problem and returns the regression coefficients.
solveTranspose(Complex[]) - Method in class com.imsl.math.ComplexLU: Return the solution x of the linear system .
solveTranspose(double[]) - Method in class com.imsl.math.LU: Return the solution x of the linear system .
sqrt(Complex) - Static method in class com.imsl.math.Complex: Returns the square root of a Complex, with a branch cut along the negative real axis.
sqrt(double) - Static method in class com.imsl.math.JMath: Returns the square root of a double.
standardDeviation(double[]) - Static method in class com.imsl.stat.Summary: Returns the population standard deviation of the given data set.
standardDeviation(double[], double[]) - Static method in class com.imsl.stat.Summary: Returns the population standard deviation of the given data set and associated weights.
start(Chart) - Method in class com.imsl.chart.Draw: Called just before a chart is drawn.
startErrorBar() - Method in class com.imsl.chart.Draw: Start drawing an error bar.
startErrorBar() - Method in class com.imsl.chart.DrawMap
startErrorBar() - Method in class com.imsl.chart.DrawPick: Start ErrorBar
startFill() - Method in class com.imsl.chart.Draw: Start drawing a filled region.
startFill() - Method in class com.imsl.chart.DrawMap
startFill() - Method in class com.imsl.chart.DrawPick: Fill
startImage() - Method in class com.imsl.chart.Draw: Start drawing an image.
startImage() - Method in class com.imsl.chart.DrawMap
startImage() - Method in class com.imsl.chart.DrawPick: Start Image
startLine() - Method in class com.imsl.chart.Draw: Start drawing lines.
startLine() - Method in class com.imsl.chart.DrawMap: Start drawing lines.
startLine() - Method in class com.imsl.chart.DrawPick: Start drawing lines.
startMarker() - Method in class com.imsl.chart.Draw: Start drawing markers.
startMarker() - Method in class com.imsl.chart.DrawMap: Start drawing markers.
startMarker() - Method in class com.imsl.chart.DrawPick: Start drawing markers.
startText() - Method in class com.imsl.chart.Draw: Start drawing text.
startText() - Method in class com.imsl.chart.DrawMap
startText() - Method in class com.imsl.chart.DrawPick: Start drawing text
stop() - Method in class com.imsl.chart.Draw: Called when a chart is finished being drawn.
stringToObject(Class, String) - Method in class com.imsl.chart.xml.ChartXML: Converts a String into an Object of the given class.
studentsT(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the Student's t cumulative probability distribution function.
subtract(Complex, Complex) - Static method in class com.imsl.math.Complex: Returns the difference of two Complex objects, x-y.
subtract(Complex, double) - Static method in class com.imsl.math.Complex: Returns the difference of a Complex object and a double, x-y.
subtract(double, Complex) - Static method in class com.imsl.math.Complex: Returns the difference of a double and a Complex object, x-y.
subtract(Complex[][], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Subtract two Complex rectangular arrays, a - b.
subtract(double[][], double[][]) - Static method in class com.imsl.math.Matrix: Subtract two rectangular arrays, a - b.
subtract(Physical, Physical) - Static method in class com.imsl.math.Physical: Subtract two compatible Physical objects.
suffix - Static variable in class com.imsl.math.Complex: String used in converting Complex to String.
syd(double, double, int, int) - Static method in class com.imsl.finance.Finance: Returns the depreciation of an asset using the sum-of-years digits method.

T

TANH - Static variable in interface com.imsl.datamining.neural.Activation: The hyperbolic tangent activation function, $g(x)=tanh{x}= frac{e^x-e^{-x}}{e^x+e^{-x}}$ .
TEMPERATURE - Static variable in class com.imsl.math.Physical
TEXT - Static variable in class com.imsl.chart.Draw
TEXT_X_CENTER - Static variable in class com.imsl.chart.ChartNode: Value for attribute "TextAlignment" indicating that the text should be centered.
TEXT_X_LEFT - Static variable in class com.imsl.chart.ChartNode: Value for attribute "TextAlignment" indicating that the text should be left adjusted.
TEXT_X_RIGHT - Static variable in class com.imsl.chart.ChartNode: Value for attribute "TextAlignment" indicating that the text should be right adjusted.
TEXT_Y_BOTTOM - Static variable in class com.imsl.chart.ChartNode: Value for attribute "TextAlignment" indicating that the text should be drawn on the baseline.
TEXT_Y_CENTER - Static variable in class com.imsl.chart.ChartNode: Value for attribute "TextAlignment" indicating that the text should be vertically centered.
TEXT_Y_TOP - Static variable in class com.imsl.chart.ChartNode: Value for attribute "TextAlignment" indicating that the text should be drawn with the top of the letters touching the top of the drawing region.
TIE_AVERAGE - Static variable in class com.imsl.stat.Ranks: In case of ties, use the average of the scores of the tied observations.
TIE_HIGHEST - Static variable in class com.imsl.stat.Ranks: In case of ties, use the highest score in the group of ties.
TIE_LOWEST - Static variable in class com.imsl.stat.Ranks: In case of ties, use the lowest score in the group of ties.
TIE_RANDOM - Static variable in class com.imsl.stat.Ranks: In case of ties, use one of the group of ties chosen at random.
TIME - Static variable in class com.imsl.math.Physical
TRANSFORM_ASIN_SQRT - Static variable in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Flag to indicate the arcsine square root transform will be applied to the percentages.
TRANSFORM_CUSTOM - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that the axis using a custom transformation.
TRANSFORM_LINEAR - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that the axis uses linear scaling.
TRANSFORM_LOG - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that the axis uses logarithmic scaling.
TRANSFORM_NONE - Static variable in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Flag to indicate no transformation of percentages.
TRANSFORM_SQRT - Static variable in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Flag to indicate the square root transform will be applied to the percentages.
TableMultiWay - class com.imsl.stat.TableMultiWay.: Tallies observations into a multi-way frequency table.
TableMultiWay(double[][], int) - Constructor for class com.imsl.stat.TableMultiWay: Constructor for TableMultiWay.
TableMultiWay(double[][], int[]) - Constructor for class com.imsl.stat.TableMultiWay: Constructor for TableMultiWay.
TableMultiWay.BalancedTable - class com.imsl.stat.TableMultiWay.BalancedTable.: Tallies the number of unique values of each variable.
TableMultiWay.UnbalancedTable - class com.imsl.stat.TableMultiWay.UnbalancedTable.: Tallies the frequency of each cell in x.
TableOneWay - class com.imsl.stat.TableOneWay.: Tallies observations into a one-way frequency table.
TableOneWay(double[], int) - Constructor for class com.imsl.stat.TableOneWay: Constructor for TableOneWay.
TableTwoWay - class com.imsl.stat.TableTwoWay.: Tallies observations into a two-way frequency table.
TableTwoWay(double[], int, double[], int) - Constructor for class com.imsl.stat.TableTwoWay: Constructor for TableTwoWay.
Text - class com.imsl.chart.Text.: The value of the attribute "Title".
Text(String) - Constructor for class com.imsl.chart.Text: Construct a Text object.
Text(String, int) - Constructor for class com.imsl.chart.Text: Construct a Text object with specified alignment.
Text(Format, double) - Constructor for class com.imsl.chart.Text: Creates a text object by applying a java.text.Format to a double.
TimeSeriesClassFilter - class com.imsl.datamining.neural.TimeSeriesClassFilter.: Converts time series data contained within nominal categories to a lagged format for processing by a neural network.
TimeSeriesClassFilter(int) - Constructor for class com.imsl.datamining.neural.TimeSeriesClassFilter: Constructor for TimeSeriesClassFilter.
TimeSeriesFilter - class com.imsl.datamining.neural.TimeSeriesFilter.: Converts time series data to a lagged format used as input to a neural network.
TimeSeriesFilter() - Constructor for class com.imsl.datamining.neural.TimeSeriesFilter: Constructor for TimeSeriesClassFilter.
Tokenizer - class com.imsl.io.Tokenizer.: Breaks a line into tokens.
Tokenizer(String, char, boolean) - Constructor for class com.imsl.io.Tokenizer: Creates a Tokenizer.
ToolTip - class com.imsl.chart.ToolTip.: A ToolTip for a chart element.
ToolTip(ChartNode) - Constructor for class com.imsl.chart.ToolTip: Creates a ToolTip node that enables ToolTips on charts.
Trainer - interface com.imsl.datamining.neural.Trainer.: Interface implemented by classes used to train a network.
Transform - interface com.imsl.chart.Transform.: Defines a custom transformation along an axis.
TransformDate - class com.imsl.chart.TransformDate.: Defines a transformation along an axis that skips weekend dates.
TransformDate() - Constructor for class com.imsl.chart.TransformDate
tan(Complex) - Static method in class com.imsl.math.Complex: Returns the tangent of a Complex.
tan(double) - Static method in class com.imsl.math.JMath: Returns the tangent of a double.
tanh(Complex) - Static method in class com.imsl.math.Complex: Returns the hyperbolic tanh of a Complex.
tanh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the hyperbolic tangent of its argument.
tbilleq(GregorianCalendar, GregorianCalendar, double) - Static method in class com.imsl.finance.Bond: Returns the bond-equivalent yield of a Treasury bill.
tbillprice(GregorianCalendar, GregorianCalendar, double) - Static method in class com.imsl.finance.Bond: Returns the price, per $100 face value, of a Treasury bill.
tbillyield(GregorianCalendar, GregorianCalendar, double) - Static method in class com.imsl.finance.Bond: Returns the yield of a Treasury bill.
textAngle - Variable in class com.imsl.chart.Draw
textColor - Variable in class com.imsl.chart.Draw
textFont - Variable in class com.imsl.chart.Draw
throwIllegalArgumentException(String, String, Object[]) - Static method in class com.imsl.Messages: Throws an IllegalArgumentException with a formatted String argument.
toString() - Method in class com.imsl.chart.AbstractChartNode: Returns the name of this ChartNode
toString() - Method in class com.imsl.math.Complex: Returns a String representation for the specified Complex.
toString() - Method in class com.imsl.math.Physical: Returns a String containing the value and units, if any.
train(Trainer, double[][], int[]) - Method in class com.imsl.datamining.neural.BinaryClassification: Trains the classification neural network using supplied trainer and patterns.
train(Network, double[][], double[][]) - Method in class com.imsl.datamining.neural.EpochTrainer: Trains the neural network using supplied training patterns.
train(Network, double[][], double[][]) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Trains the neural network using supplied training patterns.
train(Trainer, double[][], int[]) - Method in class com.imsl.datamining.neural.MultiClassification: Trains the classification neural network using supplied training patterns.
train(Network, double[][], double[][]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Trains the neural network using supplied training patterns.
train(Network, double[][], double[][]) - Method in interface com.imsl.datamining.neural.Trainer: Trains the neural network using supplied training patterns.
translate(int, int) - Method in class com.imsl.chart.Draw: Translates the origin to the point (x,y)
translate(int, int) - Method in class com.imsl.chart.DrawMap: Translates the origin to the point (x,y)
translate(int, int) - Method in class com.imsl.chart.DrawPick: Translates the origin to the point (x,y)
transpose(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Return the transpose of a Complex matrix.
transpose(double[][]) - Static method in class com.imsl.math.Matrix: Return the transpose of a matrix.
trim() - Method in class com.imsl.chart3d.BufferedPaint: Returns a subimage with the white space trimmed off.

U

UNBOUNDED_Z_SCORE_SCALING_MEAN_STDEV - Static variable in class com.imsl.datamining.neural.ScaleFilter: Flag to indicate unbounded z-score scaling using the mean and standard deviation.
UNBOUNDED_Z_SCORE_SCALING_MEDIAN_MAD - Static variable in class com.imsl.datamining.neural.ScaleFilter: Flag to indicate unbounded z-score scaling using the median and mean absolute difference.
UNWEIGHTED_LEAST_SQUARES - Static variable in class com.imsl.stat.FactorAnalysis: Indicates unweighted least squares method.
UPPER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix: This flag as the argument to setMatrixType, indicates that only the upper triangular elements of the matrix are to be printed.
UnsupervisedNominalFilter - class com.imsl.datamining.neural.UnsupervisedNominalFilter.: Converts nominal data into a series of binary encoded columns for input to a neural network.
UnsupervisedNominalFilter(int) - Constructor for class com.imsl.datamining.neural.UnsupervisedNominalFilter: Constructor for UnsupervisedNominalFilter.
UnsupervisedOrdinalFilter - class com.imsl.datamining.neural.UnsupervisedOrdinalFilter.: Encodes ordinal data into percentages for input to a neural network.
UnsupervisedOrdinalFilter(int, int) - Constructor for class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Constructor for UnsupervisedOrdinalFilter.
UserBasisRegression - class com.imsl.stat.UserBasisRegression.: Generates summary statistics using user supplied functions in a nonlinear regression model
UserBasisRegression(RegressionBasis, int, boolean) - Constructor for class com.imsl.stat.UserBasisRegression: Constructs a UserBasisRegression object
uniform(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the uniform cumulative probability distribution function.
unitsString() - Method in class com.imsl.math.Physical: Returns a String containing the units only.
unordered(double, double) - Static method in class com.imsl.math.IEEE: Unordered test on a pair of doubles.
update(Graphics) - Method in class com.imsl.chart.Chart
update() - Method in class com.imsl.chart3d.Data: Update the surface by reevaluation of the z-function and the color function.
update(double[]) - Method in class com.imsl.math.Cholesky: Updates the factorization by adding a rank-1 matrix.
update(double[], double) - Method in class com.imsl.math.RadialBasis: Adds a data point with weight = 1.
update(double[], double, double) - Method in class com.imsl.math.RadialBasis: Adds a data point with a specified weight.
update(double[][], double[]) - Method in class com.imsl.math.RadialBasis: Adds a set of data points, all with weight = 1.
update(double[][], double[], double[]) - Method in class com.imsl.math.RadialBasis: Adds a set of data points with user-specified weights.
update(double[], double[]) - Method in class com.imsl.stat.ChiSquaredTest: Adds new observations to the test.
update(double, double) - Method in class com.imsl.stat.ChiSquaredTest: Adds a new observation to the test.
update(double[][]) - Method in class com.imsl.stat.DiscriminantAnalysis: Processes a set of observations and performs a linear or quadratic discriminant function analysis among the several known groups.
update(double[][], int) - Method in class com.imsl.stat.DiscriminantAnalysis: Processes a set of observations and performs a linear or quadratic discriminant function analysis among the several known groups.
update(double[][], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis: Processes a set of observations and performs a linear or quadratic discriminant function analysis among the several known groups.
update(double[][], double[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis: Processes a set of observations and associated frequencies and weights then performs a linear or quadratic discriminant function analysis among the several known groups.
update(double[][], int, int[]) - Method in class com.imsl.stat.DiscriminantAnalysis: Processes a set of observations and performs a linear or quadratic discriminant function analysis among the several known groups.
update(double[][], int, double[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis: Processes a set of observations and associated frequencies and weights then performs a linear or quadratic discriminant function analysis among the several known groups.
update(double[][], int[], double[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis: Processes a set of observations and associated frequencies and weights then performs a linear or quadratic discriminant function analysis among the several known groups.
update(double[][], int, int[], double[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis: Processes a set of observations and associated frequencies and weights then performs a linear or quadratic discriminant function analysis among the several known groups.
update(double[], double[][], double[][]) - Method in class com.imsl.stat.KalmanFilter: Performs computation of the update equations.
update(double[], double) - Method in class com.imsl.stat.LinearRegression: Updates the regression object with a new observation.
update(double[], double, double) - Method in class com.imsl.stat.LinearRegression: Updates the regression object with a new observation and weight.
update(double[][], double[]) - Method in class com.imsl.stat.LinearRegression: Updates the regression object with a new set of observations.
update(double[][], double[], double[]) - Method in class com.imsl.stat.LinearRegression: Updates the regression object with a new set of observations and weights.
update(double[], double[]) - Method in class com.imsl.stat.NormTwoSample: Concatenates samples x and y to the samples provided in the constructor.
update(double) - Method in class com.imsl.stat.Summary: Adds an observation to the Summary object.
update(double, double) - Method in class com.imsl.stat.Summary: Adds an observation and associated weight to the Summary object.
update(double[]) - Method in class com.imsl.stat.Summary: Adds a set of observations to the Summary object.
update(double[], double[]) - Method in class com.imsl.stat.Summary: Adds a set of observations and associated weights to the Summary object.
update(double, double, double) - Method in class com.imsl.stat.UserBasisRegression: Adds a new observation and associated weight to the RegressionBasis object.
updateArray(String, Array) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an Array value.
updateArray(int, Array) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an Array value.
updateAsciiStream(int, InputStream, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an ascii stream value.
updateAsciiStream(String, InputStream, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an ascii stream value.
updateBigDecimal(int, BigDecimal) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a java.math.BigDecimal value.
updateBigDecimal(String, BigDecimal) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a java.sql.BigDecimal value.
updateBinaryStream(int, InputStream, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a binary stream value.
updateBinaryStream(String, InputStream, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a binary stream value.
updateBlob(int, Blob) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an java.sql.Blob value.
updateBlob(String, Blob) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an java.sql.Blob value.
updateBoolean(int, boolean) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a boolean value.
updateBoolean(String, boolean) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a boolean value.
updateByte(int, byte) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a byte value.
updateByte(String, byte) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a byte value.
updateBytes(int, byte[]) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a byte array value.
updateBytes(String, byte[]) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a byte value.
updateCharacterStream(int, Reader, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a character stream value.
updateCharacterStream(String, Reader, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a character stream value.
updateClob(String, Clob) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an java.sql.Clob value.
updateClob(int, Clob) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an java.sql.Clob value.
updateDate(int, Date) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a java.sql.Date value.
updateDate(String, Date) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a java.sql.Date value.
updateDouble(int, double) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a double value.
updateDouble(String, double) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a double value.
updateFloat(int, float) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a float value.
updateFloat(String, float) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a float value.
updateInt(int, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an int value.
updateInt(String, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an int value.
updateLong(int, long) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a long value.
updateLong(String, long) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a long value.
updateNull(int) - Method in class com.imsl.io.AbstractFlatFile: Gives a nullable column a null value.
updateNull(String) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a null value.
updateObject(int, Object, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an Object value.
updateObject(int, Object) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an Object value.
updateObject(String, Object, int) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an Object value.
updateObject(String, Object) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an Object value.
updateRef(String, Ref) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an java.sql.Ref value.
updateRef(int, Ref) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with an java.sql.Ref value.
updateRow() - Method in class com.imsl.io.AbstractFlatFile: Updates the underlying database with the new contents of the current row of this ResultSet object.
updateShort(int, short) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a short value.
updateShort(String, short) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a short value.
updateString(int, String) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a String value.
updateString(String, String) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a String value.
updateTime(int, Time) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a java.sql.Time value.
updateTime(String, Time) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a java.sql.Time value.
updateTimestamp(int, Timestamp) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a java.sql.Timestamp value.
updateTimestamp(String, Timestamp) - Method in class com.imsl.io.AbstractFlatFile: Updates the designated column with a java.sql.Timestamp value.
updateX(double[]) - Method in class com.imsl.stat.NormTwoSample: Concatenates the values in x to the first sample provided in the constructor.
updateY(double[]) - Method in class com.imsl.stat.NormTwoSample: Concatenates the values in y to the second sample provided in the constructor.

V

VARIANCE_COVARIANCE_MATRIX - Static variable in class com.imsl.stat.Covariances: Indicates variance-covariance matrix.
VARIANCE_COVARIANCE_MATRIX - Static variable in class com.imsl.stat.FactorAnalysis: Indicates variance-covariance matrix.
Version - class com.imsl.Version.: Print the version information.
Version() - Constructor for class com.imsl.Version
validateLink(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Checks that a Link between two Nodes is valid.
value(double) - Method in class com.imsl.math.BSpline: Returns the value of the B-spline at a point.
value(double[]) - Method in class com.imsl.math.BSpline: Returns the value of the B-spline at each point of an array.
value - Variable in class com.imsl.math.Physical
value(double[]) - Method in class com.imsl.math.RadialBasis: Returns the value of the radial basis approximation at a point.
value(double[][]) - Method in class com.imsl.math.RadialBasis: Returns the value of the radial basis at a point.
value(double) - Method in class com.imsl.math.Spline: Returns the value of the spline at a point.
value(double[]) - Method in class com.imsl.math.Spline: Returns the value of the spline at each point of an array.
valueOf(String) - Static method in class com.imsl.math.Complex: Parses a String into a Complex.
variance(double[]) - Static method in class com.imsl.stat.Summary: Returns the population variance of the given data set.
variance(double[], double[]) - Static method in class com.imsl.stat.Summary: Returns the population variance of the given data set and associated weights.
vdb(double, double, int, int, int, double, boolean) - Static method in class com.imsl.finance.Finance: Returns the depreciation of an asset for any given period using the variable-declining balance method.
verticalStripe(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a vertically striped pattern.
vnorm(double[], double[], double[]) - Method in class com.imsl.math.OdeRungeKutta: Returns the norm of a vector.

W

WHITE_BLUE_LINEAR - Static variable in interface com.imsl.chart.Colormap: Linear blue/white colormap.
Warning - class com.imsl.Warning.: Handle warning messages.
Warning() - Constructor for class com.imsl.Warning
WarningObject - class com.imsl.WarningObject.: Handle warning messages.
WarningObject() - Constructor for class com.imsl.WarningObject
Weibull(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the Weibull cumulative probability distribution function.
WeibullProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the Weibull probability density function.
WilcoxonRankSum - class com.imsl.stat.WilcoxonRankSum.: Performs a Wilcoxon rank sum test.
WilcoxonRankSum(double[], double[]) - Constructor for class com.imsl.stat.WilcoxonRankSum: Constructor for WilcoxonRankSum.
warning(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML: Receive notification of a warning.
wasNull() - Method in class com.imsl.io.AbstractFlatFile: Reports whether the last column read had a value of SQL NULL.
weight - Variable in class com.imsl.math.BsLeastSquares: The weight array of length n, where n is the number of data points fit.
write(String, String) - Method in class com.imsl.chart3d.Canvas3DChart: Write the canvas as an image file after it is next redrawn.
writePNG(OutputStream, int, int) - Method in class com.imsl.chart.Chart: Writes the chart as an PNG file.
writeSVG(Writer, boolean) - Method in class com.imsl.chart.Chart: Writes the chart as an SVG file.

X

xirr(double[], Date[]) - Static method in class com.imsl.finance.Finance: Returns the internal rate of return for a schedule of cash flows.
xirr(double[], Date[], double) - Static method in class com.imsl.finance.Finance: Returns the internal rate of return for a schedule of cash flows with a user supplied initial guess.
xnpv(double, double[], Date[]) - Static method in class com.imsl.finance.Finance: Returns the present value for a schedule of cash flows.

Y

Y(double, double, int) - Static method in class com.imsl.math.Bessel: Evaluate a sequence of Bessel functions of the second kind with real nonnegative order and real positive argument.
yearfrac(GregorianCalendar, GregorianCalendar, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the fraction of a year represented by the number of whole days between two dates.
yield(GregorianCalendar, GregorianCalendar, double, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the yield of a security that pays periodic interest.
yielddisc(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the annual yield of a discount bond.
yieldmat(GregorianCalendar, GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the annual yield of a security that pays interest at maturity.

Z

ZeroFunction - class com.imsl.math.ZeroFunction.: Muller's method to find the zeros of a univariate function, f(x).
ZeroFunction() - Constructor for class com.imsl.math.ZeroFunction: Creates an instance of the solver.
ZeroFunction.Function - interface com.imsl.math.ZeroFunction.Function.: Public interface for the user supplied function to ZeroFunction.
ZeroPolynomial - class com.imsl.math.ZeroPolynomial.: The ZeroPolynomial class computes the zeros of a polynomial with complex coefficients, Aberth's method.
ZeroPolynomial() - Constructor for class com.imsl.math.ZeroPolynomial: Creates an instance of the solver.
ZeroPolynomial.DidNotConvergeException - exception com.imsl.math.ZeroPolynomial.DidNotConvergeException.: The iteration did not converge
ZeroPolynomial.DidNotConvergeException(String) - Constructor for class com.imsl.math.ZeroPolynomial.DidNotConvergeException
ZeroPolynomial.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.math.ZeroPolynomial.DidNotConvergeException
ZeroSystem - class com.imsl.math.ZeroSystem.: Solves a system of n nonlinear equations f(x) = 0 using a modified Powell hybrid algorithm.
ZeroSystem(int) - Constructor for class com.imsl.math.ZeroSystem: Creates an object to find the zeros of a system of n equations.
ZeroSystem.DidNotConvergeException - exception com.imsl.math.ZeroSystem.DidNotConvergeException.: The iteration did not converge.
ZeroSystem.DidNotConvergeException(String) - Constructor for class com.imsl.math.ZeroSystem.DidNotConvergeException
ZeroSystem.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.math.ZeroSystem.DidNotConvergeException
ZeroSystem.Function - interface com.imsl.math.ZeroSystem.Function.: Public interface for user supplied function to ZeroSystem object.
ZeroSystem.Jacobian - interface com.imsl.math.ZeroSystem.Jacobian.: Public interface for user supplied function to ZeroSystem object.
ZeroSystem.ToleranceTooSmallException - exception com.imsl.math.ZeroSystem.ToleranceTooSmallException.: Tolerance too small
ZeroSystem.ToleranceTooSmallException(String, Object[]) - Constructor for class com.imsl.math.ZeroSystem.ToleranceTooSmallException
ZeroSystem.TooManyIterationsException - exception com.imsl.math.ZeroSystem.TooManyIterationsException.: Too many iterations.
ZeroSystem.TooManyIterationsException() - Constructor for class com.imsl.math.ZeroSystem.TooManyIterationsException
ZeroSystem.TooManyIterationsException(String, Object[]) - Constructor for class com.imsl.math.ZeroSystem.TooManyIterationsException
ZeroSystem.TooManyIterationsException(Object[]) - Constructor for class com.imsl.math.ZeroSystem.TooManyIterationsException

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Overview

Package

Class

Tree

Index

Help

JMSL^TM Numerical Library 4.0

PREV NEXT

FRAMES NO FRAMES