|SampleKolmogorovSmirnovTest Method (Distribution)|
public TestResult KolmogorovSmirnovTest( Distribution distribution )
Public Function KolmogorovSmirnovTest ( distribution As Distribution ) As TestResult
public: TestResult^ KolmogorovSmirnovTest( Distribution^ distribution )
member KolmogorovSmirnovTest : distribution : Distribution -> TestResult
The null hypothesis of the Kolmogorov-Smirnov (KS) test is that the sample is drawn from the given continuous distribution. The test statsitic 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 asympototic 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.