The multilinear normal distribution: Introduction and some basic properties

In this paper, the multilinear normal distribution is introduced as an extension of the matrix-variate normal distribution. Basic properties such as marginal and conditional distributions, moments, and the characteristic function, are also presented. A trilinear example is used to explain the genera...

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Bibliographic Details
Published in:Journal of multivariate analysis 2013-01, Vol.113 (S1), p.37-47
Main Authors: Ohlson, Martin, Rauf Ahmad, M., von Rosen, Dietrich
Format: Article
Language:English
Subjects:
Algorithms
Flip-flop algorithm
Marginal and conditional distributions
MATEMATIK
MATHEMATICS
Matrix
Matrix normal distribution
Maximum likelihood estimators
Moments
Multivariate analysis
Normal distribution
Parameter estimation
Probability Theory and Statistics
Sannolikhetsteori och statistik
Studies
Tensor product
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Summary:In this paper, the multilinear normal distribution is introduced as an extension of the matrix-variate normal distribution. Basic properties such as marginal and conditional distributions, moments, and the characteristic function, are also presented. A trilinear example is used to explain the general contents at a simpler level. The estimation of parameters using a flip-flop algorithm is also briefly discussed.
ISSN:0047-259X
1095-7243
1095-7243
DOI:10.1016/j.jmva.2011.05.015