A note on joint mix random vectors

Yugu Xiao, Jing Yao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This note studies the dependence of joint mix random vectors from the perspective of covariance matrix. We first provide two useful methods in simulations to construct joint mix for Normal distribution. Then, we propose to characterize joint mix by covariance matrix for general marginal distribution. We present some examples showing that our methodology could provide supplementary results to relevant studies in literature.

Original languageEnglish
Pages (from-to)3063-3072
Number of pages10
JournalCommunications in Statistics - Theory and Methods
Issue number12
Early online date3 Apr 2019
Publication statusPublished - 17 Jun 2020


  • copula
  • covariance matrix
  • Dependence
  • joint mixability

ASJC Scopus subject areas

  • Statistics and Probability


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