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Distribution of Sum of Squares and Products Matrices for the Generalized Multilinear Matrix-T Model

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  • Khan, Shahjahan

Abstract

The generalized multilinear model with the matrix-T error distribution is introduced in this paper. The sum of squares and products (SSP) matrix, as a counterpart of the Wishart matrix for the multinormal model, and the regression matrix for the errors and the observed as well as future responses are defined. The distributions of the regression matrix as well as the SSP matrix, and the prediction distribution of the future regression matrix and the future SSP matrix are derived.

Suggested Citation

  • Khan, Shahjahan, 2002. "Distribution of Sum of Squares and Products Matrices for the Generalized Multilinear Matrix-T Model," Journal of Multivariate Analysis, Elsevier, vol. 83(1), pages 124-140, October.
    • Handle: RePEc:eee:jmvana:v:83:y:2002:i:1:p:124-140
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    References listed on IDEAS

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    1. Prucha, Ingmar R & Kelejian, Harry H, 1984. "The Structure of Simultaneous Equation Estimators: A Generalization towards Nonnormal Disturbances," Econometrica, Econometric Society, vol. 52(3), pages 721-736, May.
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    Cited by:

    1. Bodnar, Taras & Mazur, Stepan & Okhrin, Yarema, 2013. "On the exact and approximate distributions of the product of a Wishart matrix with a normal vector," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 70-81.
    2. Kibria, B.M. Golam, 2006. "The matrix-t distribution and its applications in predictive inference," Journal of Multivariate Analysis, Elsevier, vol. 97(3), pages 785-795, March.
    3. Liu, Jin Shan & Ip, Wai Cheung & Wong, Heung, 2009. "Predictive inference for singular multivariate elliptically contoured distributions," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1440-1446, August.

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