Covariance components selection in high-dimensional growth curve model with random coefficients

In this paper, the true number of covariance components in a high-dimensional growth curve model with random coefficients are selected. We propose a selection criterion based on a concept from information theory. The proposed criterion satisfies a consistency property of the true covariance components in our high-dimensional setting. The performance of the proposed methodology is illustrated in a simulation study.

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Year of publication:	2015
Authors:	Imori, Shinpei ; Rosen, Dietrich von
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 136.2015, C, p. 86-94
Publisher:	Elsevier
Subject:	Covariance components analysis \| Generalized information criterion \| Growth curve model with random coefficients

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

Persistent link: https://www.econbiz.de/10011208480