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An Improved Evaluation of Kolmogorovs Distribution

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  • Carvalho, Luis

Abstract

We propose a new algorithm for computing extreme probabilities of Kolmogorov's goodness-of-fit measure, Dn . This algorithm is an improved version of the method originally proposed by Wang, Tsang, and Marsaglia (2003) based on a result from Durbin (1973). The new algorithm keeps the same numerical precision of the Wang et al. (2003) method, but is more efficient: it features linear instead of quadratic space complexity and has better time complexity for a common range of input parameters of practical importance. The proposed method is implemented in the R package kolmim, which also includes an improved routine to perform one-sample two-sided exact Kolmogorov-Smirnov tests.

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  • Carvalho, Luis, 2015. "An Improved Evaluation of Kolmogorovs Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(c03).
    • Handle: RePEc:jss:jstsof:v:065:c03
    DOI: http://hdl.handle.net/10.18637/jss.v065.c03
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    1. Marsaglia, George & Tsang, Wai Wan & Wang, Jingbo, 2003. "Evaluating Kolmogorov's Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i18).
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    Cited by:

    1. Franco Salerno, 2023. "The Greta Thunberg Effect on Climate Equity: A Worldwide Google Trend Analysis," Sustainability, MDPI, vol. 15(7), pages 1-13, April.

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