A coordinate-free approach of estimation in mixed linear models - Beganu, Gabriela
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The existence conditions of both the best linear unbiased estimator of expected mean and the best quadratic unbiased estimators of covariance components in multivariate mixed linear models are presented in this book by using a coordinate-free approach. These conditions are extended to a family of multivariate growth curve models. The use of the coordinate-free approach of estimation offers an attractive computational form and allows to define certain finite dimensional Hilbert spaces corresponding to the considered models.

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Produktbeschreibung
The existence conditions of both the best linear unbiased estimator of expected mean and the best quadratic unbiased estimators of covariance components in multivariate mixed linear models are presented in this book by using a coordinate-free approach. These conditions are extended to a family of multivariate growth curve models. The use of the coordinate-free approach of estimation offers an attractive computational form and allows to define certain finite dimensional Hilbert spaces corresponding to the considered models.
Autorenporträt
Professor Gabriela Beganu developed her research work in the field of Probability Theory and Mathematical Statistics. She is the author of several graduate books dedicated to her students and worked in different projects. She also published articles in reputed mathematical journals.