Some results on parameter estimation in extended growth curve models
Identifieur interne : 001F20 ( Main/Exploration ); précédent : 001F19; suivant : 001F21Some results on parameter estimation in extended growth curve models
Auteurs : Qi-Guang Wu [République populaire de Chine]Source :
- Journal of Statistical Planning and Inference [ 0378-3758 ] ; 2000.
Abstract
In this paper, estimation of parameters in extended growth curve models with arbitrary covariance matrix or uniform covariance structure or serial covariance structure is studied. Admissibility and minimaxity of the least-squares estimator of regression coefficients under matrix loss are derived. The necessary and sufficient existence conditions are obtained for the uniformly minimum risk equivariant (UMRE) estimator of regression coefficients under an affine group and a transitive group of transformations with quadratic loss and matrix loss, respectively. It is proved that no UMRE estimators of the covariance matrix V and the trace of V exist. The maximum likelihood estimator of parameters under some conditions is also discussed.
Url:
DOI: 10.1016/S0378-3758(00)00084-7
Affiliations:
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<front><div type="abstract" xml:lang="en">In this paper, estimation of parameters in extended growth curve models with arbitrary covariance matrix or uniform covariance structure or serial covariance structure is studied. Admissibility and minimaxity of the least-squares estimator of regression coefficients under matrix loss are derived. The necessary and sufficient existence conditions are obtained for the uniformly minimum risk equivariant (UMRE) estimator of regression coefficients under an affine group and a transitive group of transformations with quadratic loss and matrix loss, respectively. It is proved that no UMRE estimators of the covariance matrix V and the trace of V exist. The maximum likelihood estimator of parameters under some conditions is also discussed.</div>
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