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

Sammanfattning

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. (C) 2015 Elsevier Inc. All rights reserved.

Nyckelord

Covariance components analysis; Generalized information criterion; Growth curve model with random coefficients

Publicerad i

Journal of Multivariate Analysis
2015, volym: 136, sidor: 86-94

SLU författare

• von Rosen, Dietrich

  • Institutionen för energi och teknik, Sveriges lantbruksuniversitet
    
  • Linköpings universitet

UKÄ forskningsämne

Sannolikhetsteori och statistik

Publikationens identifierare

• DOI: https://doi.org/10.1016/j.jmva.2015.01.010

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/73451