A fast algorithm for two-dimensional Kolmogorov–Smirnov two sample tests

Yuanhui Xiao

Computational Statistics & Data Analysis, 2017, vol. 105, issue C, 53-58

Abstract: By using the brute force algorithm, the application of the two-dimensional two-sample Kolmogorov–Smirnov test can be prohibitively computationally expensive. Thus a fast algorithm for computing the two-sample Kolmogorov–Smirnov test statistic is proposed to alleviate this problem. The newly proposed algorithm is O(n) times more efficient than the brute force algorithm, where n is the sum of the two sample sizes. The proposed algorithm is parallel and can be generalized to higher dimensional spaces.

Keywords: Kolmogorov–Smirnov test; Brute force algorithm (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:105:y:2017:i:c:p:53-58

DOI: 10.1016/j.csda.2016.07.014

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