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Covariance components selection in high-dimensional growth curve model with random coefficients
Osaka University, Japan.
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, The Institute of Technology. Swedish University of Agriculture Science, Sweden.
2015 (English)In: Journal of Multivariate Analysis, ISSN 0047-259X, E-ISSN 1095-7243, Vol. 136, 86-94 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier , 2015. Vol. 136, 86-94 p.
Keyword [en]
Covariance components analysis; Generalized information criterion; Growth curve model with random coefficients
National Category
URN: urn:nbn:se:liu:diva-117650DOI: 10.1016/j.jmva.2015.01.010ISI: 000352182100007OAI: diva2:811555

Funding Agencies|JSPS

Available from: 2015-05-12 Created: 2015-05-06 Last updated: 2015-05-12

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von Rosen, Dietrich
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Mathematical Statistics The Institute of Technology
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