E-Book, Englisch, 268 Seiten, eBook
Reihe: Use R!
Albert Bayesian Computation with R
2007
ISBN: 978-0-387-71385-4
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 268 Seiten, eBook
Reihe: Use R!
ISBN: 978-0-387-71385-4
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
Bayesian Computation with R introduces Bayesian modeling by the use of computation using the R language. Early chapters present the basic tenets of Bayesian thinking by use of familiar one and two-parameter inferential problems. Bayesian computational methods such as Laplace's method, rejection sampling, and the SIR algorithm are illustrated in the context of a random effects model. The construction and implementation of Markov Chain Monte Carlo (MCMC) methods is introduced. These simulation-based algorithms are implemented for a variety of Bayesian applications such as normal and binary response regression, hierarchical modeling, order-restricted inference, and robust modeling.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Weitere Infos & Material
An Introduction to R.- to Bayesian Thinking.- Single-Parameter Models.- Multiparameter Models.- to Bayesian Computation.- Markov Chain Monte Carlo Methods.- Hierarchical Modeling.- Model Comparison.- Regression Models.- Gibbs Sampling.- Using R to Interface with WinBUGS.
