Artículos relacionados a Bayesian Model Selection and Statistical Modeling (Statistic...

Bayesian Model Selection and Statistical Modeling (Statistics: Textbooks and Monographs) - Tapa blanda

Libro 39 de 88: Statistics: A Series of Textbooks and Monographs

Ando, Tomohiro

 
9780367383978: Bayesian Model Selection and Statistical Modeling (Statistics: Textbooks and Monographs)
Tapa blanda
ISBN 10: 0367383977 ISBN 13: 9780367383978
Editorial: Routledge, 2019

Sinopsis

Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model selection procedures. It thoroughly explains the concepts, illustrates the derivations of various Bayesian model selection criteria through examples, and provides R code for implementation.

The author shows how to implement a variety of Bayesian inference using R and sampling methods, such as Markov chain Monte Carlo. He covers the different types of simulation-based Bayesian model selection criteria, including the numerical calculation of Bayes factors, the Bayesian predictive information criterion, and the deviance information criterion. He also provides a theoretical basis for the analysis of these criteria. In addition, the author discusses how Bayesian model averaging can simultaneously treat both model and parameter uncertainties.

Selecting and constructing the appropriate statistical model significantly affect the quality of results in decision making, forecasting, stochastic structure explorations, and other problems. Helping you choose the right Bayesian model, this book focuses on the framework for Bayesian model selection and includes practical examples of model selection criteria.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Tomohiro Ando is an associate professor of management science in the Graduate School of Business Administration at Keio University in Japan.

De la contraportada

Along with many practical applications, this book presents an array of Bayesian inference and model selection procedures. It thoroughly explains the concepts, illustrates the derivations of various Bayesian model selection criteria through examples, and provides R code for implementation. The R code is available for download on the book's website. The text also applies Bayesian model averaging to many problems and compares the different types of simulation-based Bayesian model selection criteria, including the numerical calculation of Bayes factors, the Bayesian predictive information criterion, and the deviance information criterion.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Routledge
Año de publicación
2019
Idioma
Inglés
ISBN 10 
0367383977
ISBN 13 
9780367383978
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
300
Contacto del fabricante
Taylor and Francis, GPSR Taylor and Francis
gpsr@taylorandfrancis.com

Taylor & Francis Verlag GmbH, Kaufingerstraße 24
München
80331
Alemania