Volume 5, Issue 2 (11-2010)
IJMSI 2010, 5(2): 33-43 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Iranmanesh A, Arashi M, Tabatabaey S M M. On Conditional Applications of Matrix Variate Normal Distribution. IJMSI 2010; 5 (2) :33-43
URL: http://ijmsi.ir/article-1-139-en.html
URL: http://ijmsi.ir/article-1-139-en.html
Abstract:
In this paper, by conditioning on the matrix variate normal distribution (MVND) the construction of the matrix t-type family is considered, thus providing a new perspective of this family. Some important statistical characteristics are given. The presented t-type family is an extension to the work of Dickey [8]. A Bayes estimator for the column covariance matrix &Sigma of MVND is derived under Kullback Leibler divergence loss (KLDL). Further an application of the proposed result is given in the Bayesian context of the multivariate linear model. It is illustrated that the Bayes estimators of coefficient matrix under both SEL and KLDL are identical.
Keywords: Bayes estimator, Characteristic function, Generalized matrix t-distribution, Kullback Leibler divergence loss, Matrix variate gamma distribution, Matrix variate normal distribution.
Type of Study: Research paper |
Subject:
General
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
