fr.cnes.sirius.patrius.math.stat.inference

Class TestUtils

java.lang.Object

fr.cnes.sirius.patrius.math.stat.inference.TestUtils

public final class TestUtils
extends Object

A collection of static methods to create inference test instances or to perform inference tests.

Since:

1.1

Version:

$Id: TestUtils.java 18108 2017-10-04 06:45:27Z bignon $

Method Summary

Modifier and Type	Method and Description
static double	chiSquare(double[] expected, long[] observed)
static double	chiSquare(long[][] counts)
static double	chiSquareDataSetsComparison(long[] observed1, long[] observed2)
static double	chiSquareTest(double[] expected, long[] observed)
static boolean	chiSquareTest(double[] expected, long[] observed, double alpha)
static double	chiSquareTest(long[][] counts)
static boolean	chiSquareTest(long[][] counts, double alpha)
static double	chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)
static boolean	chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
static double	g(double[] expected, long[] observed)
static double	gDataSetsComparison(long[] observed1, long[] observed2)
static double	gTest(double[] expected, long[] observed)
static boolean	gTest(double[] expected, long[] observed, double alpha)
static double	gTestDataSetsComparison(long[] observed1, long[] observed2)
static boolean	gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
static double	gTestIntrinsic(double[] expected, long[] observed)
static double	homoscedasticT(double[] sample1, double[] sample2)
static double	homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) See TTest# homoscedasticT(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)
static double	homoscedasticTTest(double[] sample1, double[] sample2)
static boolean	homoscedasticTTest(double[] sample1, double[] sample2, double alpha)
static double	homoscedasticTTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) See TTest# homoscedasticTTest(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)
static double	oneWayAnovaFValue(Collection<double[]> categoryData)
static double	oneWayAnovaPValue(Collection<double[]> categoryData)
static boolean	oneWayAnovaTest(Collection<double[]> categoryData, double alpha)
static double	pairedT(double[] sample1, double[] sample2)
static double	pairedTTest(double[] sample1, double[] sample2)
static boolean	pairedTTest(double[] sample1, double[] sample2, double alpha)
static double	rootLogLikelihoodRatio(long k11, long k12, long k21, long k22)
static double	t(double[] sample1, double[] sample2)
static double	t(double mu, double[] observed)
static double	t(double mu, StatisticalSummary sampleStats)
static double	t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) See TTest# t(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)
static double	tTest(double[] sample1, double[] sample2)
static boolean	tTest(double[] sample1, double[] sample2, double alpha)
static double	tTest(double mu, double[] sample)
static boolean	tTest(double mu, double[] sample, double alpha)
static double	tTest(double mu, StatisticalSummary sampleStats)
static boolean	tTest(double mu, StatisticalSummary sampleStats, double alpha)
static double	tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) See fr.cnes.sirius.patrius.math.stat.inference.TTest# tTest(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)
static boolean	tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha) See fr.cnes.sirius.patrius.math.stat.inference.TTest# tTest(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, double)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

homoscedasticT

public static double homoscedasticT(double[] sample1,
                                    double[] sample2)

Parameters:

sample1 - array of sample data values

sample2 - array of sample data values

Returns:

t statistic

See Also:

TTest.homoscedasticT(double[], double[])

homoscedasticT

public static double homoscedasticT(StatisticalSummary sampleStats1,
                                    StatisticalSummary sampleStats2)

See TTest# homoscedasticT(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)

Parameters:

sampleStats1 - StatisticalSummary describing data from the first sample

sampleStats2 - StatisticalSummary describing data from the second sample

Returns:

t statistic

homoscedasticTTest

public static boolean homoscedasticTTest(double[] sample1,
                                         double[] sample2,
                                         double alpha)

Parameters:

sample1 - array of sample data values

sample2 - array of sample data values

alpha - significance level of the test

Returns:

true if the null hypothesis can be rejected with confidence 1 - alpha

See Also:

TTest.homoscedasticTTest(double[], double[], double)

homoscedasticTTest

public static double homoscedasticTTest(double[] sample1,
                                        double[] sample2)

Parameters:

sample1 - array of sample data values

sample2 - array of sample data values

Returns:

t statistic

See Also:

TTest.homoscedasticTTest(double[], double[])

homoscedasticTTest

public static double homoscedasticTTest(StatisticalSummary sampleStats1,
                                        StatisticalSummary sampleStats2)

See TTest# homoscedasticTTest(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)

Parameters:

sampleStats1 - StatisticalSummary describing data from the first sample

sampleStats2 - StatisticalSummary describing data from the second sample

Returns:

t statistic

pairedT

public static double pairedT(double[] sample1,
                             double[] sample2)

Parameters:

sample1 - array of sample data values

sample2 - array of sample data values

Returns:

t statistic

See Also:

TTest.pairedT(double[], double[])

pairedTTest

public static boolean pairedTTest(double[] sample1,
                                  double[] sample2,
                                  double alpha)

Parameters:

sample1 - array of sample data values

sample2 - array of sample data values

alpha - significance level of the test

Returns:

true if the null hypothesis can be rejected with confidence 1 - alpha

See Also:

TTest.pairedTTest(double[], double[], double)

pairedTTest

public static double pairedTTest(double[] sample1,
                                 double[] sample2)

Parameters:

sample1 - array of sample data values

sample2 - array of sample data values

Returns:

t statistic

See Also:

TTest.pairedTTest(double[], double[])

t

public static double t(double mu,
                       double[] observed)

Parameters:

mu - comparison constant

observed - array of values

Returns:

t statistic

See Also:

TTest.t(double, double[])

t

public static double t(double mu,
                       StatisticalSummary sampleStats)

Parameters:

mu - comparison constant

sampleStats - DescriptiveStatistics holding sample summary statitstics

Returns:

t statistic

See Also:

TTest.t(double, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)

t

public static double t(double[] sample1,
                       double[] sample2)

Parameters:

sample1 - array of sample data values

sample2 - array of sample data values

Returns:

t statistic

See Also:

TTest.t(double[], double[])

t

public static double t(StatisticalSummary sampleStats1,
                       StatisticalSummary sampleStats2)

See TTest# t(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)

Parameters:

sampleStats1 - StatisticalSummary describing data from the first sample

sampleStats2 - StatisticalSummary describing data from the second sample

Returns:

t statistic

tTest

public static boolean tTest(double mu,
                            double[] sample,
                            double alpha)

Parameters:

mu - constant value to compare sample mean against

sample - array of sample data values

alpha - significance level of the test

Returns:

p-value

See Also:

TTest.tTest(double, double[], double)

tTest

public static double tTest(double mu,
                           double[] sample)

Parameters:

mu - constant value to compare sample mean against

sample - array of sample data values

Returns:

p-value

See Also:

TTest.tTest(double, double[])

tTest

public static boolean tTest(double mu,
                            StatisticalSummary sampleStats,
                            double alpha)

Parameters:

mu - constant value to compare sample mean against

sampleStats - StatisticalSummary describing sample data values

alpha - significance level of the test

Returns:

p-value

See Also:

TTest.tTest(double, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, double)

tTest

public static double tTest(double mu,
                           StatisticalSummary sampleStats)

Parameters:

mu - constant value to compare sample mean against

sampleStats - StatisticalSummary describing sample data

Returns:

p-value

See Also:

TTest.tTest(double, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)

tTest

public static boolean tTest(double[] sample1,
                            double[] sample2,
                            double alpha)

Parameters:

sample1 - array of sample data values

sample2 - array of sample data values

alpha - significance level of the test

Returns:

true if the null hypothesis can be rejected with confidence 1 - alpha

See Also:

TTest.tTest(double[], double[], double)

tTest

public static double tTest(double[] sample1,
                           double[] sample2)

Parameters:

sample1 - array of sample data values

sample2 - array of sample data values

Returns:

t statistic

See Also:

TTest.tTest(double[], double[])

tTest

public static boolean tTest(StatisticalSummary sampleStats1,
                            StatisticalSummary sampleStats2,
                            double alpha)

See fr.cnes.sirius.patrius.math.stat.inference.TTest# tTest(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, double)

Parameters:

sampleStats1 - StatisticalSummary describing data from the first sample

sampleStats2 - StatisticalSummary describing data from the second sample

alpha - significance level of the test

Returns:

true if the null hypothesis can be rejected with confidence 1 - alpha

tTest

public static double tTest(StatisticalSummary sampleStats1,
                           StatisticalSummary sampleStats2)

See fr.cnes.sirius.patrius.math.stat.inference.TTest# tTest(fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary, fr.cnes.sirius.patrius.math.stat.descriptive.StatisticalSummary)

Parameters:

sampleStats1 - StatisticalSummary describing data from the first sample

sampleStats2 - StatisticalSummary describing data from the second sample

Returns:

t statistic

chiSquare

public static double chiSquare(double[] expected,
                               long[] observed)

Parameters:

observed - array of observed frequency counts

expected - array of expected frequency counts

Returns:

chiSquare test statistic

See Also:

ChiSquareTest.chiSquare(double[], long[])

chiSquare

public static double chiSquare(long[][] counts)

Parameters:

counts - array representation of 2-way table

Returns:

chiSquare test statistic

See Also:

ChiSquareTest.chiSquare(long[][])

chiSquareTest

public static boolean chiSquareTest(double[] expected,
                                    long[] observed,
                                    double alpha)

Parameters:

observed - array of observed frequency counts

expected - array of expected frequency counts

alpha - significance level of the test

Returns:

true iff null hypothesis can be rejected with confidence 1 - alpha

See Also:

ChiSquareTest.chiSquareTest(double[], long[], double)

chiSquareTest

public static double chiSquareTest(double[] expected,
                                   long[] observed)

Parameters:

observed - array of observed frequency counts

expected - array of expected frequency counts

Returns:

p-value

See Also:

ChiSquareTest.chiSquareTest(double[], long[])

chiSquareTest

public static boolean chiSquareTest(long[][] counts,
                                    double alpha)

Parameters:

counts - array representation of 2-way table

alpha - significance level of the test

Returns:

true iff null hypothesis can be rejected with confidence 1 - alpha

See Also:

ChiSquareTest.chiSquareTest(long[][], double)

chiSquareTest

public static double chiSquareTest(long[][] counts)

Parameters:

counts - array representation of 2-way table

Returns:

p-value

See Also:

ChiSquareTest.chiSquareTest(long[][])

chiSquareDataSetsComparison

public static double chiSquareDataSetsComparison(long[] observed1,
                                                 long[] observed2)

Parameters:

observed1 - array of observed frequency counts of the first data set

observed2 - array of observed frequency counts of the second data set

Returns:

chiSquare test statistic

Since:

1.2

See Also:

ChiSquareTest.chiSquareDataSetsComparison(long[], long[])

chiSquareTestDataSetsComparison

public static double chiSquareTestDataSetsComparison(long[] observed1,
                                                     long[] observed2)

Parameters:

observed1 - array of observed frequency counts of the first data set

observed2 - array of observed frequency counts of the second data set

Returns:

p-value

Since:

1.2

See Also:

ChiSquareTest.chiSquareTestDataSetsComparison(long[], long[])

chiSquareTestDataSetsComparison

public static boolean chiSquareTestDataSetsComparison(long[] observed1,
                                                      long[] observed2,
                                                      double alpha)

Parameters:

observed1 - array of observed frequency counts of the first data set

observed2 - array of observed frequency counts of the second data set

alpha - significance level of the test

Returns:

true iff null hypothesis can be rejected with confidence 1 - alpha

Since:

1.2

See Also:

ChiSquareTest.chiSquareTestDataSetsComparison(long[], long[], double)

oneWayAnovaFValue

public static double oneWayAnovaFValue(Collection<double[]> categoryData)

Parameters:

categoryData - Collection of double[] arrays each containing data for one category

Returns:

Fvalue

Since:

1.2

See Also:

OneWayAnova.anovaFValue(Collection)

oneWayAnovaPValue

public static double oneWayAnovaPValue(Collection<double[]> categoryData)

Parameters:

categoryData - Collection of double[] arrays each containing data for one category

Returns:

Pvalue

Since:

1.2

See Also:

OneWayAnova.anovaPValue(Collection)

oneWayAnovaTest

public static boolean oneWayAnovaTest(Collection<double[]> categoryData,
                                      double alpha)

Parameters:

categoryData - Collection of double[] arrays each containing data for one category

alpha - significance level of the test

Returns:

true if the null hypothesis can be rejected with confidence 1 - alpha

Since:

1.2

See Also:

OneWayAnova.anovaTest(Collection,double)

g

public static double g(double[] expected,
                       long[] observed)

Parameters:

observed - array of observed frequency counts

expected - array of expected frequency counts

Returns:

G-Test statistic

Since:

3.1

See Also:

GTest.g(double[], long[])

gTest

public static double gTest(double[] expected,
                           long[] observed)

Parameters:

observed - array of observed frequency counts

expected - array of expected frequency counts

Returns:

p-value

Since:

3.1

See Also:

GTest.gTest(double[], long[] )

gTestIntrinsic

public static double gTestIntrinsic(double[] expected,
                                    long[] observed)

Parameters:

observed - array of observed frequency counts

expected - array of expected frequency counts

Returns:

p-value

Since:

3.1

See Also:

GTest.gTestIntrinsic(double[], long[] )

gTest

public static boolean gTest(double[] expected,
                            long[] observed,
                            double alpha)

Parameters:

observed - array of observed frequency counts

expected - array of expected frequency counts

alpha - significance level of the test

Returns:

true iff null hypothesis can be rejected with confidence 1 - alpha

Since:

3.1

See Also:

GTest.gTest(double[],long[],double)

gDataSetsComparison

public static double gDataSetsComparison(long[] observed1,
                                         long[] observed2)

Parameters:

observed1 - array of observed frequency counts of the first data set

observed2 - array of observed frequency counts of the second data set

Returns:

G-Test statistic

Since:

3.1

See Also:

GTest.gDataSetsComparison(long[], long[])

rootLogLikelihoodRatio

public static double rootLogLikelihoodRatio(long k11,
                                            long k12,
                                            long k21,
                                            long k22)

Parameters:

k11 - number of times the two events occurred together (AB)

k12 - number of times the second event occurred WITHOUT the first event (notA,B)

k21 - number of times the first event occurred WITHOUT the second event (A, notB)

k22 - number of times something else occurred (i.e. was neither of these events (notA, notB)

Returns:

root log-likelihood ratio

Since:

3.1

See Also:

GTest.rootLogLikelihoodRatio(long, long, long, long)

gTestDataSetsComparison

public static double gTestDataSetsComparison(long[] observed1,
                                             long[] observed2)

Parameters:

observed1 - array of observed frequency counts of the first data set

observed2 - array of observed frequency counts of the second data set

Returns:

p-value

Since:

3.1

See Also:

GTest.gTestDataSetsComparison(long[], long[])

gTestDataSetsComparison

public static boolean gTestDataSetsComparison(long[] observed1,
                                              long[] observed2,
                                              double alpha)

Parameters:

observed1 - array of observed frequency counts of the first data set

observed2 - array of observed frequency counts of the second data set

alpha - significance level of the test

Returns:

true iff null hypothesis can be rejected with confidence 1 - alpha

Since:

3.1

See Also:

GTest.gTestDataSetsComparison(long[],long[],double)