|
||||||||||
PREV NEXT | FRAMES NO FRAMES |
Packages that use DataIsEmptyException | |
---|---|
edu.ucla.stat.SOCR.analyses.model | |
edu.ucla.stat.SOCR.util |
Uses of DataIsEmptyException in edu.ucla.stat.SOCR.analyses.model |
---|
Methods in edu.ucla.stat.SOCR.analyses.model that throw DataIsEmptyException | |
---|---|
Result |
TwoPairedT.analyze(Data data,
short analysisType)
|
Result |
TwoPairedSignedRank.analyze(Data data,
short analysisType)
|
Result |
TwoIndependentWilcoxon.analyze(Data data,
short analysisType)
|
Result |
TwoIndependentT.analyze(Data data,
short analysisType)
|
Result |
TwoIndependentKruskalWallis.analyze(Data data,
short analysisType)
|
Result |
TwoIndependentFriedman.analyze(Data data,
short analysisType)
|
Result |
Survival.analyze(Data data,
short analysisType)
|
Result |
SimpleLinearRegression.analyze(Data data,
short analysisType)
|
Result |
OneZ.analyze(Data data,
short analysisType)
|
Result |
OneT.analyze(Data data,
short analysisType)
|
Result |
NormalPower.analyze(Data data,
short analysisType)
|
Result |
MultiLinearRegression.analyze(Data data,
short analysisType)
|
Result |
LogisticRegression.analyze(Data data,
short analysisType)
|
Result |
KolmogorovSmirnoff.analyze(Data data,
short analysisType)
|
Result |
FlignerKilleen.analyze(Data data,
short analysisType)
|
Result |
FisherExact.analyze(Data data,
short analysisType)
|
Result |
ChiSquareContingencyTable.analyze(Data data,
short analysisType)
|
Result |
AnovaTwoWay.analyze(Data data,
short analysisType)
|
Result |
AnovaOneWay.analyze(Data data,
short analysisType)
|
static double[] |
Regression.diff(double[] data)
|
static double |
Regression.mean(double[] data)
|
static double |
Regression.sampleCovariance(double[] dataX,
double[] dataY)
|
static double |
Regression.sampleVariance(double[] data)
|
static double |
Regression.sumOfSquares(double[] data)
|
Uses of DataIsEmptyException in edu.ucla.stat.SOCR.util |
---|
Methods in edu.ucla.stat.SOCR.util that throw DataIsEmptyException | |
---|---|
static double[] |
AnalysisUtility.diff(double[] data)
|
static double[] |
RandomGenerator.getGeneratedArray(double[] input,
int distribution)
|
static double[] |
AnalysisUtility.getStandardizedResidual(DataCase[] residual,
int df)
|
static double[] |
AnalysisUtility.getStandardizedResidual(double[] residual,
int degreesFreedom)
|
static double |
AnalysisUtility.mean(double[] data)
|
static double |
AnalysisUtility.meanSquaredError(double[] data,
int degreesFreedom)
|
static java.math.BigInteger |
AnalysisUtility.product(java.math.BigInteger[] data)
|
static double |
AnalysisUtility.product(double[] data)
|
static double |
AnalysisUtility.sampleCorrelation(double[] dataX,
double[] dataY)
|
static double |
AnalysisUtility.sampleCovariance(double[] dataX,
double[] dataY)
|
static double |
AnalysisUtility.sampleVariance(double[] data)
|
static double |
AnalysisUtility.sum(double[] data)
|
static double |
AnalysisUtility.sumOfSquares(double[] data)
|
static double |
AnalysisUtility.variance(double[] data)
|
|
||||||||||
PREV NEXT | FRAMES NO FRAMES |