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Moments for a multivariate linear model with an application to the growth curve model

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  • von Rosen, Dietrich

Abstract

An extended growth curve model is considered which, among other things, is useful when linear restrictions exist on the mean in the ordinary growth curve model. The maximum likelihood estimators consist of complicated stochastic expressions. It is shown how, by the aid of fairly elementary calculations, the dispersion matrix for the estimator of the mean and the expectation of the estimated dispersion matrix are obtained. Results for Wishart, inverted Wishart, and inverse beta variables are utilized. Additionally, some asymptotic results are presented.

Suggested Citation

  • von Rosen, Dietrich, 1990. "Moments for a multivariate linear model with an application to the growth curve model," Journal of Multivariate Analysis, Elsevier, vol. 35(2), pages 243-259, November.
    • Handle: RePEc:eee:jmvana:v:35:y:1990:i:2:p:243-259
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    Cited by:

    1. Hamid Jemila S & Beyene Joseph, 2009. "A Multivariate Growth Curve Model for Ranking Genes in Replicated Time Course Microarray Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-26, July.
    2. Jian-Xin Pan & Kai-Tai Fang, 1996. "Influential observation in the growth curve model with unstructured covariance matrix," Computational Statistics & Data Analysis, Elsevier, vol. 22(1), pages 71-87, June.
    3. Hamid, Jemila S. & Beyene, Joseph & von Rosen, Dietrich, 2011. "A novel trace test for the mean parameters in a multivariate growth curve model," Journal of Multivariate Analysis, Elsevier, vol. 102(2), pages 238-251, February.

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