Sinossi
Nonlinear mixed effects models involve both fixed effects and random effects in which some of the fixed and random effects parameters enter nonlinearly to the model function. These models are become very popular for analyzing clustered data or unbalanced repeated measures data that occur in various fields of scientific investigation, such as pharmacokinetics, agriculture, biochemistry, environment, economics, etc. Because of the extensive use of nonlinear mixed effects models, there are several different methods for estimating the parameters of these models. Most of the proposed methods are based on the approximation technique because of the intractable multidimensional integrations arise in the likelihood function of the nonlinear mixed effects models. In this study, instead of approximation based methods we use quasi-Monte Carlo integration method using different types of quasi-random sequences, which directly solves the intractable multidimensional integrations.
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Estimation of Nonlinear Mixed Effects Model
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LAP LAMBERT Academic Publishing Jun 2016, 2016
ISBN 10: 3659909076
ISBN 13: 9783659909078
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Nonlinear mixed effects models involve both fixed effects and random effects in which some of the fixed and random effects parameters enter nonlinearly to the model function. These models are become very popular for analyzing clustered data or unbalanced repeated measures data that occur in various fields of scientific investigation, such as pharmacokinetics, agriculture, biochemistry, environment, economics, etc. Because of the extensive use of nonlinear mixed effects models, there are several different methods for estimating the parameters of these models. Most of the proposed methods are based on the approximation technique because of the intractable multidimensional integrations arise in the likelihood function of the nonlinear mixed effects models. In this study, instead of approximation based methods we use quasi-Monte Carlo integration method using different types of quasi-random sequences, which directly solves the intractable multidimensional integrations. 72 pp. Englisch. Codice articolo 9783659909078
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Estimation of Nonlinear Mixed Effects Model
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ISBN 10: 3659909076
ISBN 13: 9783659909078
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Das SukantaI am Sukanta Das I am currently working as a Statistical Officer at Bangladesh Inland Water Transport Authority (BIWTA). I received my Graduation (B.Sc.) and Post-Graduation (M.Sc.) degree in Applied Statistics form the I. Codice articolo 385770578
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Estimation of Nonlinear Mixed Effects Model: Using Quasi-Random Sequences
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659909076
ISBN 13: 9783659909078
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Paperback. Condizione: Brand New. 72 pages. 8.66x5.91x0.17 inches. In Stock. Codice articolo 3659909076
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Estimation of Nonlinear Mixed Effects Model
Editore:
LAP LAMBERT Academic Publishing Jun 2016, 2016
ISBN 10: 3659909076
ISBN 13: 9783659909078
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Nonlinear mixed effects models involve both fixed effects and random effects in which some of the fixed and random effects parameters enter nonlinearly to the model function. These models are become very popular for analyzing clustered data or unbalanced repeated measures data that occur in various fields of scientific investigation, such as pharmacokinetics, agriculture, biochemistry, environment, economics, etc. Because of the extensive use of nonlinear mixed effects models, there are several different methods for estimating the parameters of these models. Most of the proposed methods are based on the approximation technique because of the intractable multidimensional integrations arise in the likelihood function of the nonlinear mixed effects models. In this study, instead of approximation based methods we use quasi-Monte Carlo integration method using different types of quasi-random sequences, which directly solves the intractable multidimensional integrations.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch. Codice articolo 9783659909078
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Estimation of Nonlinear Mixed Effects Model : Using Quasi-Random Sequences
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659909076
ISBN 13: 9783659909078
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Nonlinear mixed effects models involve both fixed effects and random effects in which some of the fixed and random effects parameters enter nonlinearly to the model function. These models are become very popular for analyzing clustered data or unbalanced repeated measures data that occur in various fields of scientific investigation, such as pharmacokinetics, agriculture, biochemistry, environment, economics, etc. Because of the extensive use of nonlinear mixed effects models, there are several different methods for estimating the parameters of these models. Most of the proposed methods are based on the approximation technique because of the intractable multidimensional integrations arise in the likelihood function of the nonlinear mixed effects models. In this study, instead of approximation based methods we use quasi-Monte Carlo integration method using different types of quasi-random sequences, which directly solves the intractable multidimensional integrations. Codice articolo 9783659909078
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Estimation of Nonlinear Mixed Effects Model | Using Quasi-Random Sequences
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659909076
ISBN 13: 9783659909078
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Taschenbuch. Condizione: Neu. Estimation of Nonlinear Mixed Effects Model | Using Quasi-Random Sequences | Sukanta Das (u. a.) | Taschenbuch | 72 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659909078 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 103577235
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