Publication | Open Access
Evaluating Kolmogorov's Distribution
972
Citations
4
References
2003
Year
EngineeringData ScienceUncertainty QuantificationEntropyStatistical FoundationGoodness-of-fit MeasureProbabilistic AnalysisStatistical ComputingSample CdfStatistical InferenceProbability TheoryC ProcedureMathematical StatisticKolmogorov ComplexityStatistics
Kolmogorov's goodness-of-fit measure, D<sub>n</sub> , for a sample CDF has consistently been set aside for methods such as the D<sup>+</sup><sub>n</sub> or D<sup>-</sup><sub>n</sub> of Smirnov, primarily, it seems, because of the difficulty of computing the distribution of D<sub>n</sub> . As far as we know, no easy way to compute that distribution has ever been provided in the 70+ years since Kolmogorov's fundamental paper. We provide one here, a C procedure that provides Pr(D<sub>n</sub> < d) with 13-15 digit accuracy for n ranging from 2 to at least 16000. We assess the (rather slow) approach to limiting form, and because computing time can become excessive for probabilities>.999 with n's of several thousand, we provide a quick approximation that gives accuracy to the 7th digit for such cases.
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