A family of kurtosis orderings for multivariate distributions

Jin Wang

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


In this paper, a family of kurtosis orderings for multivariate distributions is proposed and studied. Each ordering characterizes in an affine invariant sense the movement of probability mass from the "shoulders" of a distribution to either the center or the tails or both. All even moments of the Mahalanobis distance of a random vector from its mean (if exists) preserve a subfamily of the orderings. For elliptically symmetric distributions, each ordering determines the distributions up to affine equivalence. As applications, the orderings are used to study elliptically symmetric distributions. Ordering results are established for three important families of elliptically symmetric distributions: Kotz type distributions, Pearson Type VII distributions, and Pearson Type II distributions.

Original languageEnglish (US)
Pages (from-to)509-517
Number of pages9
JournalJournal of Multivariate Analysis
Issue number3
StatePublished - Mar 2009


  • 62G05
  • 62H05
  • Elliptically symmetric distributions
  • Kurtosis
  • Ordering
  • Peakedness
  • Tailweight
  • primary
  • secondary

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty


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