Bayesian statistical inference on elliptical matrix distributions

Kai Tai Fang; Runze Li

doi:10.1006/jmva.1998.1816

Bayesian statistical inference on elliptical matrix distributions

Kai Tai Fang
, Runze Li

Research output: Contribution to journal › Article › peer-review

29 Scopus citations

Abstract

In this paper we are concerned with Bayesian statistical inference for a class of elliptical distributions with parameters μ and Σ. Under a noninformative prior distribution, we obtain the posterior distribution, posterior mean, and generalized maximim likelihood estimators of μ and Σ. Under the entropy loss and quadratic loss, the best Bayesian estimators of Σ are derived as well. Some applications are given.

Original language	English (US)
Pages (from-to)	66-85
Number of pages	20
Journal	Journal of Multivariate Analysis
Volume	70
Issue number	1
DOIs	https://doi.org/10.1006/jmva.1998.1816
State	Published - Jul 1999

All Science Journal Classification (ASJC) codes

Statistics and Probability
Numerical Analysis
Statistics, Probability and Uncertainty

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10.1006/jmva.1998.1816

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title = "Bayesian statistical inference on elliptical matrix distributions",

abstract = "In this paper we are concerned with Bayesian statistical inference for a class of elliptical distributions with parameters μ and Σ. Under a noninformative prior distribution, we obtain the posterior distribution, posterior mean, and generalized maximim likelihood estimators of μ and Σ. Under the entropy loss and quadratic loss, the best Bayesian estimators of Σ are derived as well. Some applications are given.",

author = "Fang, \{Kai Tai\} and Runze Li",

note = "Funding Information: * This work was supported by a Hong Kong RGC grant, the Statistical Ressearch and Consultancy Centre, Hong Kong Baptist University.",

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AU - Li, Runze

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Y1 - 1999/7

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AB - In this paper we are concerned with Bayesian statistical inference for a class of elliptical distributions with parameters μ and Σ. Under a noninformative prior distribution, we obtain the posterior distribution, posterior mean, and generalized maximim likelihood estimators of μ and Σ. Under the entropy loss and quadratic loss, the best Bayesian estimators of Σ are derived as well. Some applications are given.

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M3 - Article

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EP - 85

JO - Journal of Multivariate Analysis

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Bayesian statistical inference on elliptical matrix distributions

Abstract

All Science Journal Classification (ASJC) codes

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