Covariance components selection in high-dimensional growth curve model with random coefficients
2015 (English)In: Journal of Multivariate Analysis, ISSN 0047-259X, E-ISSN 1095-7243, Vol. 136, 86-94 p.Article in journal (Refereed) Published
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.
Covariance components analysis; Generalized information criterion; Growth curve model with random coefficients
IdentifiersURN: urn:nbn:se:liu:diva-117650DOI: 10.1016/j.jmva.2015.01.010ISI: 000352182100007OAI: oai:DiVA.org:liu-117650DiVA: diva2:811555