A note on joint mix random vectors

Yugu Xiao, Jing Yao

Research output: Contribution to journalArticle

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
JournalCommunications in Statistics - Theory and Methods
Early online date3 Apr 2019
DOIs
Publication statusE-pub ahead of print - 3 Apr 2019

Fingerprint

Random Vector
Covariance matrix
Marginal Distribution
Gaussian distribution
Methodology
Simulation

Keywords

  • copula
  • covariance matrix
  • Dependence
  • joint mixability

ASJC Scopus subject areas

  • Statistics and Probability

Cite this

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title = "A note on joint mix random vectors",
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.",
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A note on joint mix random vectors. / Xiao, Yugu; Yao, Jing.

In: Communications in Statistics - Theory and Methods, 03.04.2019.

Research output: Contribution to journalArticle

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