Bayesian Inference with INLA

By Virgilio Gomez-Rubio

Subjects: Laplace transformation, Bayesian statistics, Statistical inference, Probabilities, Bayesian analysis, Statistical decision theory, Regression analysis, Mathematical statistics, Bayesian statistical decision theory

Description: Bayesian Inference with INLA provides a description of INLA and its associated R package for model fitting. This book describes the underlying methodology as well as how to fit a wide range of models with R. Topics covered include generalized linear mixed-effects models, multilevel models, spatial and spatio-temporal models, smoothing methods, survival analysis, imputation of missing values, and mixture models. Advanced features of the INLA package and how to extend the number of priors and latent models available in the package are discussed. All examples in the book are fully reproducible and datasets and R code are available from the book website.