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 general contents at a simpler level. The estimation of parameters using a flip-flop algorithm is also briefly discussed.

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Year of publication:	2013
Authors:	Ohlson, Martin ; Rauf Ahmad, M. ; von Rosen, Dietrich
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 113.2013, C, p. 37-47
Publisher:	Elsevier
Subject:	Flip-flop algorithm \| Matrix normal distribution \| Marginal and conditional distributions \| Maximum likelihood estimators \| Moments \| Tensor product

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010588052