Estimation of variance components in mixed linear models is an important problem in statistical inference to draw a valid and meaningful interpretation in many practical areas of research. ANOVA, Analogous to ANOVA, SS Approach, ML, REML, MML, MINQUE, MIVQUE and QLSE are some of the important methods available in literature for estimation of variance components in general mixed linear models. In this book we have introduced MTE, WQLSE and modified MIVQUE estimators and also derived their variances and also the covariance matrices. In fact we have presented the explicit computable expressions for the computation of MTE, WQLSE, Modified MIVQUE estimators and their covariance matrices. The relative performance of MTE, QLSE, WQLSE, MIVQUE and Modified MIVQUE estimators are assessed by numerical evaluations based on different optimality criteria like T-Optimality, D-Optimality and M-Optimality together with their variances for various n-patterns. I hope that this book may be a useful guide for the applied workers to solve their practical problems and a reference book for the researchers to do research in variance components estimation.
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Dr.J.Subramani has his Ph.D. in Statistics from University of Madras in 1991. He is the Winner of ISPS Award and the ISI 5th Competion for Young Statisticians in 1991. His research interests are in Experimental Designs, Sampling Theory, Statistical Quality Control and Recreational Mathemtics. He has more than two decades of professional experience.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Estimation of variance components in mixed linear models is an important problem in statistical inference to draw a valid and meaningful interpretation in many practical areas of research. ANOVA, Analogous to ANOVA, SS Approach, ML, REML, MML, MINQUE, MIVQUE and QLSE are some of the important methods available in literature for estimation of variance components in general mixed linear models. In this book we have introduced MTE, WQLSE and modified MIVQUE estimators and also derived their variances and also the covariance matrices. In fact we have presented the explicit computable expressions for the computation of MTE, WQLSE, Modified MIVQUE estimators and their covariance matrices. The relative performance of MTE, QLSE, WQLSE, MIVQUE and Modified MIVQUE estimators are assessed by numerical evaluations based on different optimality criteria like T-Optimality, D-Optimality and M-Optimality together with their variances for various n-patterns. I hope that this book may be a useful guide for the applied workers to solve their practical problems and a reference book for the researchers to do research in variance components estimation. 136 pp. Englisch. Bestandsnummer des Verkäufers 9783845429687
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Subramani JambulingamDr.J.Subramani has his Ph.D. in Statistics from University of Madras in 1991. He is the Winner of ISPS Award and the ISI 5th Competion for Young Statisticians in 1991. His research interests are in Experimental D. Bestandsnummer des Verkäufers 5482077
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Estimation of variance components in mixed linear models is an important problem in statistical inference to draw a valid and meaningful interpretation in many practical areas of research. ANOVA, Analogous to ANOVA, SS Approach, ML, REML, MML, MINQUE, MIVQUE and QLSE are some of the important methods available in literature for estimation of variance components in general mixed linear models. In this book we have introduced MTE, WQLSE and modified MIVQUE estimators and also derived their variances and also the covariance matrices. In fact we have presented the explicit computable expressions for the computation of MTE, WQLSE, Modified MIVQUE estimators and their covariance matrices. The relative performance of MTE, QLSE, WQLSE, MIVQUE and Modified MIVQUE estimators are assessed by numerical evaluations based on different optimality criteria like T-Optimality, D-Optimality and M-Optimality together with their variances for various n-patterns. I hope that this book may be a useful guide for the applied workers to solve their practical problems and a reference book for the researchers to do research in variance components estimation.Books on Demand GmbH, Überseering 33, 22297 Hamburg 136 pp. Englisch. Bestandsnummer des Verkäufers 9783845429687
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Estimation of variance components in mixed linear models is an important problem in statistical inference to draw a valid and meaningful interpretation in many practical areas of research. ANOVA, Analogous to ANOVA, SS Approach, ML, REML, MML, MINQUE, MIVQUE and QLSE are some of the important methods available in literature for estimation of variance components in general mixed linear models. In this book we have introduced MTE, WQLSE and modified MIVQUE estimators and also derived their variances and also the covariance matrices. In fact we have presented the explicit computable expressions for the computation of MTE, WQLSE, Modified MIVQUE estimators and their covariance matrices. The relative performance of MTE, QLSE, WQLSE, MIVQUE and Modified MIVQUE estimators are assessed by numerical evaluations based on different optimality criteria like T-Optimality, D-Optimality and M-Optimality together with their variances for various n-patterns. I hope that this book may be a useful guide for the applied workers to solve their practical problems and a reference book for the researchers to do research in variance components estimation. Bestandsnummer des Verkäufers 9783845429687
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Taschenbuch. Zustand: Neu. Estimation of Variance Components | in Mixed Linear Models | Jambulingam Subramani | Taschenbuch | 136 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845429687 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 106864452
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