Bayesian Model Selection and Statistical Modeling - Couverture souple

Ando, Tomohiro

Couverture souple

ISBN 10 : 0367383977 ISBN 13 : 9780367383978

Editeur : Routledge, 2019

Synopsis

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.

A propos du livre

À propos de l'auteur

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

À propos de la quatrième de couverture

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.

Détails de l'édition

• Éditeur: Routledge
• Date d'édition: 2019
• Langue: anglais
• ISBN 10: 0367383977
• ISBN 13: 9780367383978
• Reliure: Broché
• Nombre de pages: 286
• Coordonnées du fabricant: non disponible
• Personne responsable: gpsr@libri.de; gpsr@libri.de; ; Europaallee 1; Bad Hersfeld; 36244; Allemagne