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Mixed-Effects Models and Small Area Estimation

Af: Tatsuya Kubokawa, Shonosuke Sugasawa Engelsk Paperback

Mixed-Effects Models and Small Area Estimation

Af: Tatsuya Kubokawa, Shonosuke Sugasawa Engelsk Paperback
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This book provides a self-contained introduction of mixed-effects models and small area estimation techniques. In particular, it focuses on both introducing classical theory and reviewing the latest methods. First, basic issues of mixed-effects models, such as parameter estimation, random effects prediction, variable selection, and asymptotic theory, are introduced. Standard mixed-effects models used in small area estimation, known as the Fay-Herriot model and the nested error regression model, are then introduced. Both frequentist and Bayesian approaches are given to compute predictors of small area parameters of interest. For measuring uncertainty of the predictors, several methods to calculate mean squared errors and confidence intervals are discussed. Various advanced approaches using mixed-effects models are introduced, from frequentist to Bayesian approaches. This book is helpful for researchers and graduate students in fields requiring data analysis skills as well as in mathematical statistics.

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This book provides a self-contained introduction of mixed-effects models and small area estimation techniques. In particular, it focuses on both introducing classical theory and reviewing the latest methods. First, basic issues of mixed-effects models, such as parameter estimation, random effects prediction, variable selection, and asymptotic theory, are introduced. Standard mixed-effects models used in small area estimation, known as the Fay-Herriot model and the nested error regression model, are then introduced. Both frequentist and Bayesian approaches are given to compute predictors of small area parameters of interest. For measuring uncertainty of the predictors, several methods to calculate mean squared errors and confidence intervals are discussed. Various advanced approaches using mixed-effects models are introduced, from frequentist to Bayesian approaches. This book is helpful for researchers and graduate students in fields requiring data analysis skills as well as in mathematical statistics.

Produktdetaljer
Sprog: Engelsk
Sider: 121
ISBN-13: 9789811994852
Indbinding: Paperback
Udgave:
ISBN-10: 9811994854
Udg. Dato: 4 feb 2023
Længde: 10mm
Bredde: 233mm
Højde: 155mm
Forlag: Springer Verlag, Singapore
Oplagsdato: 4 feb 2023
Forfatter(e) Tatsuya Kubokawa, Shonosuke Sugasawa


Kategori Bayesiansk statistik


ISBN-13 9789811994852


Sprog Engelsk


Indbinding Paperback


Sider 121


Udgave


Længde 10mm


Bredde 233mm


Højde 155mm


Udg. Dato 4 feb 2023


Oplagsdato 4 feb 2023


Forlag Springer Verlag, Singapore

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