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Kolmogorov-Smirnov TestThis test is used to decide if a sample comes from a hypothesized continuous distribution. It is based on the empirical cumulative distribution function (ECDF). Assume that we have a random sample x1, ... , xn from some distribution with CDF F(x). The empirical CDF is denoted by ![]() DefinitionThe Kolmogorov-Smirnov statistic (D) is based on the largest vertical difference between the theoretical and the empirical cumulative distribution function: ![]() Hypothesis TestingThe null and the alternative hypotheses are:
The hypothesis regarding the distributional form is rejected at the chosen
significance level ( The standard tables of critical values used for this test are only valid when testing whether a data set is from a completely specified distribution. If one or more distribution parameters are estimated, the results will be conservative: the actual significance level will be smaller than that given by the standard tables, and the probability that the fit will be rejected in error will be lower. P-Value
The P-value, in contrast to fixed The P-value can be useful, in particular, when the null hypothesis is rejected at all predefined significance levels, and you need to know at which level it could be accepted. EasyFit displays the P-values based on the Kolmogorov-Smirnov test statistics (D) calculated for each fitted distribution. |
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