Maximum likelihood estimation for joint mean-covariance models from unbalanced repeated-measures data

This paper develops maximum likelihood estimates for jointly modelling the mean and covariance matrix, for unbalanced repeated measures, using an unconstrained parametrization. Furthermore, the asymptotic distribution of the estimated parameters and the results of a simulation study are presented.

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Year of publication:	2007
Authors:	Holan, Scott ; Spinka, Christine
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 77.2007, 3, p. 319-328
Publisher:	Elsevier
Keywords:	Associated populations Asymptotic normality Independent not identically distributed (i.n.i.d.) Maximum likelihood estimation Modified Cholesky decomposition Unbalanced design

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

Persistent link: https://www.econbiz.de/10005313803