Generalized Cramér-von Mises goodness-of-fit tests for multivariate distributions

Sung Nok CHIU*, Kwong Ip LIU

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

A class of statistics for testing the goodness-of-fit for any multivariate continuous distribution is proposed. These statistics consider not only the goodness-of-fit of the joint distribution but also the goodness-of-fit of all marginal distributions, and can be regarded as generalizations of the multivariate Cramér-von Mises statistic. Simulation shows that these generalizations, using the Monte Carlo test procedure to approximate their finite-sample p-values, are more powerful than the multivariate Kolmogorov-Smirnov statistic.

Original languageEnglish
Pages (from-to)3817-3834
Number of pages18
JournalComputational Statistics and Data Analysis
Volume53
Issue number11
DOIs
Publication statusPublished - 1 Sep 2009

Scopus Subject Areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

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