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 journalJournal articlepeer-review

36 Citations (Scopus)
54 Downloads (Pure)


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 -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
Issue number11
Early online date22 Apr 2009
Publication statusPublished - 1 Sept 2009

Scopus Subject Areas

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


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