A note on joint mix random vectors

Yugu Xiao, Jing Yao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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
Volume49
Issue number12
Early online date3 Apr 2019
DOIs
Publication statusPublished - 17 Jun 2020

Keywords

  • copula
  • covariance matrix
  • Dependence
  • joint mixability

ASJC Scopus subject areas

  • Statistics and Probability

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