Synopsis
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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About the Author
I 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 Institute of Statistical Research and Training, University of Dhaka, Bangladesh in the year of 2013 and 2014 respectively.
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Estimation of Nonlinear Mixed Effects Model
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Taschenbuch. Condition: 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. Seller Inventory # 9783659909078
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Estimation of Nonlinear Mixed Effects Model
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Condition: 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. Seller Inventory # 385770578
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Estimation of Nonlinear Mixed Effects Model: Using Quasi-Random Sequences
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Estimation of Nonlinear Mixed Effects Model
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Taschenbuch. Condition: 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. Seller Inventory # 9783659909078
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Estimation of Nonlinear Mixed Effects Model : Using Quasi-Random Sequences
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Taschenbuch. Condition: 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. Seller Inventory # 9783659909078
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Estimation of Nonlinear Mixed Effects Model | Using Quasi-Random Sequences
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Taschenbuch. Condition: 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. Seller Inventory # 103577235
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