An Algorithm for Computing the Exact Distribution of the Kruskal-Wallis Test

Won Choi, Jae Won Lee, Myung Hoe Huh, Seung Ho Kang

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

The Kruskal-Wallis test is a popular nonparametric test for comparing k independent samples. In this article we propose a new algorithm to compute the exact null distribution of the Kruskal-Wallis test. Generating the exact null distribution of the Kruskal-Wallis test is needed to compare several approximation methods. The 5% cut-off points of the exact null distribution which StatXact cannot produce are obtained as by-products. We also investigate graphically a reason that the exact and approximate distributions differ, and hope that it will be a useful tutorial tool to teach about the Kruskal-Wallis test in undergraduate course.

Original languageEnglish
Pages (from-to)1029-1040
Number of pages12
JournalCommunications in Statistics Part B: Simulation and Computation
Volume32
Issue number4
DOIs
Publication statusPublished - 2003 Nov 1

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Exact Distribution
Byproducts
Null Distribution
Computing
Non-parametric test
Approximation Methods

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation

Cite this

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An Algorithm for Computing the Exact Distribution of the Kruskal-Wallis Test. / Choi, Won; Lee, Jae Won; Huh, Myung Hoe; Kang, Seung Ho.

In: Communications in Statistics Part B: Simulation and Computation, Vol. 32, No. 4, 01.11.2003, p. 1029-1040.

Research output: Contribution to journalArticle

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