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JMSLTM Numerical Library 4.0 | ||||||||
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java.lang.Object com.imsl.stat.ANOVA
Analysis of Variance table and related statistics.
Constructor Summary | |
ANOVA(double[][] y)
Analyzes a one-way classification model. |
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ANOVA(double dfr,
double ssr,
double dfe,
double sse,
double gmean)
Construct an analysis of variance table and related statistics. |
Method Summary | |
double |
getAdjustedRSquared()
Returns the adjusted R-squared (in percent). |
double[] |
getArray()
Returns the ANOVA values as an array. |
double |
getCoefficientOfVariation()
Returns the coefficient of variation (in percent). |
double |
getDegreesOfFreedomForError()
Returns the degrees of freedom for error. |
double |
getDegreesOfFreedomForModel()
Returns the degrees of freedom for model. |
double |
getDunnSidak(int i,
int j)
Computes the confidence interval of i-th mean - j-th mean, using the Dunn-Sidak method. |
double |
getErrorMeanSquare()
Returns the error mean square. |
double |
getF()
Returns the F statistic. |
double[][] |
getGroupInformation()
Returns information concerning the groups. |
double |
getMeanOfY()
Returns the mean of the response (dependent variable). |
double |
getModelErrorStdev()
Returns the estimated standard deviation of the model error. |
double |
getModelMeanSquare()
Returns the model mean square. |
double |
getP()
Returns the p-value. |
double |
getRSquared()
Returns the R-squared (in percent). |
double |
getSumOfSquaresForError()
Returns the sum of squares for error. |
double |
getSumOfSquaresForModel()
Returns the sum of squares for model. |
double |
getTotalDegreesOfFreedom()
Returns the total degrees of freedom. |
int |
getTotalMissing()
Returns the total number of missing values. |
double |
getTotalSumOfSquares()
Returns the total sum of squares. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
public ANOVA(double[][] y)
y
- is a two-dimension double
array containing the
responses. The rows in y
correspond to
observation groups. Each row of y
can
contain a different number of observations.public ANOVA(double dfr, double ssr, double dfe, double sse, double gmean)
dfr
- a double
scalar value representing
the degrees of freedom for modelssr
- a double
scalar value representing the sum
of squares for modeldfe
- a double
scalar value representing the
degrees of freedom for errorsse
- a double
scalar value representing the sum
of squares for errorgmean
- a double
scalar value representing the
grand mean. If the grand mean is not known it may be
set to not-a-number.Method Detail |
public double getAdjustedRSquared()
double
scalar value representing the adjusted
R-squared (in percent)public double[] getArray()
double
[15] array containing the following values:
index | Value |
0 | Degrees of freedom for model |
1 | Degrees of freedom for error |
2 | Total degrees of freedom |
3 | Sum of squares for model |
4 | Sum of squares for error |
5 | Total sum of squares |
6 | Model mean square |
7 | Error mean square |
8 | F statistic |
9 | p-value |
10 | R-squared (in percent) |
11 | Adjusted R-squared (in percent) |
12 | Estimated standard deviation of the model error |
13 | Mean of the response (dependent variable) |
14 | Coefficient of variation (in percent) |
public double getCoefficientOfVariation()
double
scalar value representing the coefficient
of variation (in percent)public double getDegreesOfFreedomForError()
double
scalar value representing the degrees of
freedom for errorpublic double getDegreesOfFreedomForModel()
double
scalar value representing the degrees of
freedom for modelpublic double getDunnSidak(int i, int j)
i
- is a int
indicating the i-th member of
the pair, j
- is a int
indicating the j-th member of
the pair,
public double getErrorMeanSquare()
double
scalar value representing the error mean
squarepublic double getF()
double
scalar value representing the F statisticpublic double[][] getGroupInformation()
double
array containing information
concerning the groups. Row i contains information
pertaining to the i-th group. The information in the
columns is as follows:
Column | Information |
0 | Group Number |
1 | Number of nonmissing observations |
2 | Group Mean |
3 | Group Standard Deviation |
public double getMeanOfY()
double
scalar value representing the mean of the
response (dependent variable)public double getModelErrorStdev()
double
scalar value representing the estimated
standard deviation of the model errorpublic double getModelMeanSquare()
double
scalar value representing the model mean
squarepublic double getP()
double
scalar value representing the
p-valuepublic double getRSquared()
double
scalar value representing the
R-squared (in percent)public double getSumOfSquaresForError()
double
scalar value representing the sum of
squares for errorpublic double getSumOfSquaresForModel()
double
scalar value representing the sum of
squares for modelpublic double getTotalDegreesOfFreedom()
double
scalar value representing the total
degrees of freedompublic int getTotalMissing()
int
scalar value representing the total number
of missing values (NaN) in input Y. Elements of Y containing
NaN (not a number) are omitted from the computations.public double getTotalSumOfSquares()
double
scalar value representing the total sum of
squares
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JMSLTM Numerical Library 4.0 | ||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |