HypothesisTests Class

Contains static methods to create hypothesis tests.

Definition

Namespace: Extreme.Statistics
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
C# 
public static class HypothesisTests
Inheritance
Object  →  HypothesisTests

Methods

AndersonDarlingTest Returns an Anderson-Darling test whether a sample was drawn from the normal distribution.
CramerVonMisesTest(Vector<Double>, ContinuousDistribution) Returns a Cramer-von Mises test that the specified values were drawn from the specified distribution.
CramerVonMisesTest(Vector<Double>, Func<Double, Double>) Returns a Cramer-von Mises test that the specified values were drawn from a distribution with the specified distribution function.
FTest(Vector<Double>, Vector<Double>, HypothesisType) Returns an F test for the ratio of the variances of two populations.
FTest(Double, Double, Double, Double, HypothesisType) Returns an F test for the ratio of two variances.
GoodnessOfFitTest(Histogram<Double>, ContinuousDistribution, Int32)Returns a ChiSquareGoodnessOfFitTest object to test if the distribution follows the specified distribution.
GoodnessOfFitTest(Histogram<Int32>, DiscreteDistribution, Int32)Returns a ChiSquareGoodnessOfFitTest object to test if the distribution follows the specified distribution.
GoodnessOfFitTest<T>(Histogram<T>, Histogram<T>)Returns a ChiSquareGoodnessOfFitTest object to test if the distribution follows the specified distribution specified as a histogram.
KolmogorovSmirnovTest(Vector<Double>, Vector<Double>) Returns a Kolmogorov-Smirnov test whether two samples were drawn from the same distribution.
KolmogorovSmirnovTest(Vector<Double>, ContinuousDistribution) Returns a Kolmogorov-Smirnov test whether a sample was drawn from the specified distribution.
KolmogorovSmirnovTest(Vector<Double>, Func<Double, Double>) Returns a Kolmogorov-Smirnov test whether a sample was drawn from the specified distribution.
McNemarTest(ICategoricalVector, ICategoricalVector, Boolean) Returns a McNemar test whether proportions are the same in two samples.
McNemarTest<T>(IList<T>, IList<T>, Boolean) Returns a McNemar test whether proportions are the same in two samples.
PairedTTest Returns a paired TwoSampleTTest for the difference between two population means.
ShapiroWilkTest Returns a Shapiro-Wilk test whether a sample was drawn from the normal distribution.
StuartMaxwellTest Constructs a new StuartMaxwellTest.
TTest(Vector<Double>, Double, HypothesisType) Returns a new OneSampleTTest for the mean of a population.
TTest(Double, Double, Int32, Double, HypothesisType) Returns a OneSampleTTest for the mean of a population based on properties of a sample from the population.
TwoSampleZTest Constructs a new TwoSampleZTest(ICategoricalVector, ICategoricalVector, Double, HypothesisType) for the specified samples.
UnpairedTTest Returns an unpaired TwoSampleTTest for the difference between two population means.
ZTest(Vector<Double>, Double, Double, HypothesisType) Returns a Z test for the mean of a population with known variance.
ZTest(Int32, Double, Double, Double, HypothesisType) Returns a Z test for the mean of a population with known variance.
ZTest(Int32, Double, Int32, Double, Double, HypothesisType) Constructs a new TwoSampleZTest(ICategoricalVector, ICategoricalVector, Double, HypothesisType) for the difference between two proportions.

See Also