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Information Journal Paper

Title

ON CONDITIONAL APPLICATIONS OF MATRIX VARIATE NORMAL DISTRIBUTION

Pages

  33-43

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 S 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.

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    • Cite

    APA: Copy

    IRANMANESH, ANIS, ARASHI, M., & TABATABAEY, S.M.M.. (2010). ON CONDITIONAL APPLICATIONS OF MATRIX VARIATE NORMAL DISTRIBUTION. IRANIAN JOURNAL OF MATHEMATICAL SCIENCES AND INFORMATICS (IJMSI), 5(2), 33-43. SID. https://sid.ir/paper/310307/en

    Vancouver: Copy

    IRANMANESH ANIS, ARASHI M., TABATABAEY S.M.M.. ON CONDITIONAL APPLICATIONS OF MATRIX VARIATE NORMAL DISTRIBUTION. IRANIAN JOURNAL OF MATHEMATICAL SCIENCES AND INFORMATICS (IJMSI)[Internet]. 2010;5(2):33-43. Available from: https://sid.ir/paper/310307/en

    IEEE: Copy

    ANIS IRANMANESH, M. ARASHI, and S.M.M. TABATABAEY, “ON CONDITIONAL APPLICATIONS OF MATRIX VARIATE NORMAL DISTRIBUTION,” IRANIAN JOURNAL OF MATHEMATICAL SCIENCES AND INFORMATICS (IJMSI), vol. 5, no. 2, pp. 33–43, 2010, [Online]. Available: https://sid.ir/paper/310307/en

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