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:: Volume 5, Issue 2 (11-2010) ::
IJMSI 2010, 5(2): 33-43 Back to browse issues page
On Conditional Applications of Matrix Variate Normal Distribution
Anis Iranmanesh , M. Arashi , S. M. M. Tabatabaey

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.
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Type of Study: Research | Subject: General
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DOI: 10.7508/ijmsi.2010.02.004

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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
Volume 5, Issue 2 (11-2010) Back to browse issues page
نشریه علوم ریاضی و انفورماتیک Iranian Journal of Mathematical Sciences and Informatics
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