SampleKolmogorovSmirnovTest(ContinuousDistribution) Method

public TestResult KolmogorovSmirnovTest(
	ContinuousDistribution distribution
)

Public Function KolmogorovSmirnovTest ( 
	distribution As ContinuousDistribution
) As TestResult

public:
TestResult^ KolmogorovSmirnovTest(
	ContinuousDistribution^ distribution
)

member KolmogorovSmirnovTest : 
        distribution : ContinuousDistribution -> TestResult 

Parameters

distribution  ContinuousDistribution

The test distribution.

Return Value

The null hypothesis of the Kolmogorov-Smirnov (KS) test is that the sample is drawn from the given continuous distribution. The test statistic D is the maximum deviation of the sample's empirical distribution function (EDF) from the distribution's cumulative distribution function (CDF). A high value of the test statistic, corresponding to a low right tail probability, indicates that the sample distribution disagrees with the given distribution to a degree unlikely to arise from statistical fluctuations.

For small sample sizes, we compute the null distribution of D exactly. For large sample sizes, we use an accurate asymptotic approximation. Therefore it is safe to use this method for all sample sizes.

A variant of this test, KolmogorovSmirnovTest(Sample, Sample), allows you to non-parametrically test whether two samples are drawn from the same underlying distribution, without having to specify that distribution.

Reference

Other Resources