Khan, Shahjahan ORCID: https://orcid.org/0000-0002-0446-086X
(2002)
Distribution of sum of squares and products matrices for the generalized multilinear matrix-T model.
Journal of Multivariate Analysis, 83.
pp. 124-140.
ISSN 0047-259X
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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.
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Item Type: | Article (Commonwealth Reporting Category C) |
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Refereed: | Yes |
Item Status: | Live Archive |
Faculty/School / Institute/Centre: | Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013) |
Faculty/School / Institute/Centre: | Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013) |
Date Deposited: | 11 Oct 2007 00:33 |
Last Modified: | 02 Aug 2021 04:32 |
Uncontrolled Keywords: | generalized multilinear model; matrix-T distribution; sum of squares and product matrix; regression matrix; prediction distribution; Wishart distribution; invariant differentials; generalized beta and gamma distributions |
Fields of Research (2008): | 01 Mathematical Sciences > 0104 Statistics > 010499 Statistics not elsewhere classified 01 Mathematical Sciences > 0104 Statistics > 010404 Probability Theory |
Fields of Research (2020): | 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490599 Statistics not elsewhere classified 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490506 Probability theory |
Socio-Economic Objectives (2008): | E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences |
Identification Number or DOI: | https://doi.org/10.1006/jmva.2001.2040 |
URI: | http://eprints.usq.edu.au/id/eprint/1050 |
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