Exact Nonparametric Two-Sample Homogeneity Tests for Possibly Discrete Distributions

Jean-Marie Dufour () and Abdeljelil Farhat ()

Cahiers de recherche from Universite de Montreal, Departement de sciences economiques

Abstract: In this paper, we study several tests for the equality of two unknown distributions. Two are based on empirical distribution functions, three others on nonparametric probability density estimates, and the last ones on differences between sample moments. We suggest controlling the size of such tests (under nonparametric assumptions) by using permutational versions of the tests jointly with the method of Monte Carlo tests properly adjusted to deal with discrete distributions. We also propose a combined test procedure, whose level is again perfectly controlled through the Monte Carlo test technique and has better power properties than the individual tests that are combined. Finally, in a simulation experiment, we show that the technique suggested provides perfect control of test size and that the new tests proposed can yield sizeable power improvements.

Keywords: nonrametric methods; two-same oblem; discrete distribution; discontinuous distribution; goodness-of-fit test; Kolmogorov-Smirnov test; Cramér-von Mises; kernel density estimator; exact test; rmutation test; Monte Carlo test; bootstra combined test ocedure; induced test (search for similar items in EconPapers)
JEL-codes: C50 C51 C52 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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http://hdl.handle.net/1866/362 (application/pdf)

Related works:
Working Paper: Exact Nonparametric Two-Sample Homogeneity Tests for Possibly Discrete Distributions (2001)
Working Paper: Exact Nonparametric Two-Sample Homogeneity Tests for Possibly Discrete Distributions (2001)
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Persistent link: https://EconPapers.repec.org/RePEc:mtl:montde:2001-23

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