Course on Bayesian inference for latent Gaussian models  - R-INLA
    Latent Gaussian models (LGMs) are perhaps the most commonly used class of models in statistical modeling applications. It includes, among others: - ( generalized) linear mixed models - (generalized) additive models - smoothing spline models and semi-parametric regression models - spatial models
    Bayesian Regression Modeling with INLA | Taylor & Francis Group
    This book addresses the applications of extensively used regression models under a Bayesian framework. It emphasizes efficient Bayesian inference through.
    pc.prec penalization - The R-INLA project
    New book: "Bayesian Regression Modeling with INLA" Congratulations to Xiaofeng Wang, Yu Yue Ryan and Julian J Faraway, for their new book " Bayesian RegressionModelling with INLA", which is announced on Amazon and ready for preorder (at Posted 4 Jan 2018, 08:39 by Havard Rue; "A gentle INLA tutorial".
    Examples and tutorials - The R-INLA project
    Minicurso: Advances and Challenges in Space-time Modelling (17-18 June 2013 , Lisbon) · Model criticism and conflict diagnostics using R-INLA · N-Mixture models · NCSE Summer Workshop 2015: "Flexible spatial (and spatio-temporal) modelling using the SPDE approach “ · New book: "Bayesian RegressionModeling 
    Fast and accurate Bayesian model criticism and conflict  - arXiv
    Fast and accurate Bayesian model criticism and conflict diagnostics using R-INLA. Egil Ferkingstad∗1, Leonhard Held2, and Håvard Rue3. 1Science Institute, University of Iceland, Reykjavik, Iceland. 2Epidemiology, Biostatistics and Prevention Institute, University of. Zurich, Switzerland. 3CEMSE Division 
    Bayesian analysis of measurement error models using integrated
    logistic model with a binary error-free covariate and a model suffering from classical error, and an overdispersed Poisson regression model with Berkson error. In Section 3 we review classical and Berkson ME and the effects on the estimates of regression coefficients. Bayesian analysis with INLA is 
    Discussion forum - The R-INLA project
    Minicurso: Advances and Challenges in Space-time Modelling (17-18 June 2013 , Lisbon) · Model criticism and conflict diagnostics using R-INLA · N-Mixture models · NCSE Summer Workshop 2015: "Flexible spatial (and spatio-temporal) modelling using the SPDE approach “ · New book: "Bayesian RegressionModeling 
    Code for model B of salamander data - The R-INLA project
    organize data into a form suitable for logistic regression dat0=data.frame("y"=c( salam$y), "fW"=as.integer(salam$x[,"W/R"]==1 | salam$x[,"W/W"]==1), "mW"=as. integer(salam$x[,"R/W"]==1 | salam$x[,"W/W"]==1), "WW"=as.integer(salam$x[,"W /W"]==1 ) ) ## add salamander id (female, male) id = t( apply(salam$z, 1, function (x) 
    PC-priors (Simpson et al (2014, 2015, 2016)) - The R-INLA project
    Minicurso: Advances and Challenges in Space-time Modelling (17-18 June 2013 , Lisbon) · Model criticism and conflict diagnostics using R-INLA · N-Mixture models · NCSE Summer Workshop 2015: "Flexible spatial (and spatio-temporal) modelling using the SPDE approach “ · New book: "Bayesian RegressionModeling 
    Bayesian Computing with INLA: A Review - The R-INLA project
    This is the site for the INLA approach to Bayesian inference within the R project for Statistical Computing.
    Bayesian Hierarchical Models - UBC Department of Statistics
    1/ 20. R and RStudio. Statistical Analyses. Packages. R-INLA. Bayesian Hierarchical Models. Gavin Shaddick,. Millie Green, Matthew Thomas. University of Bath. 6th - 9th December 2016 
    Bayesian Regression Modeling With Inla (Hardcover) (Xiaofeng
    This book addresses the applications of extensively used regression models under a Bayesian framework. It emphasizes efficient Bayesian inference through integrated nested Laplace approximations (INLA) and real data analysis using R. The INLA method directly computes very accurate approximations to the posterior  
    INLA - arXiv
    In particular we address a simple linear latent model, a. Bayesian linearregression model, logistic Bayesian regression models with probit and logit links, and a Poisson longitudinal generalized linear mixed model. Keywords: Integrated nested Laplace approximation; Marginal likelihood; Model Evidence;.
    Code for Survival Example - The R-INLA project
    Minicurso: Advances and Challenges in Space-time Modelling (17-18 June 2013 , Lisbon) · Model criticism and conflict diagnostics using R-INLA · N-Mixture models · NCSE Summer Workshop 2015: "Flexible spatial (and spatio-temporal) modelling using the SPDE approach “ · New book: "Bayesian RegressionModeling 
    Introduction to R-INLA for Bayesian Spatial Modeling, Rome 13-15Dec
    NCSE Summer Workshop 2015: "Flexible spatial (and spatio-temporal) modelling using the SPDE approach “ · New book: "Bayesian RegressionModeling with INLA" · New comparison paper: logit mixed models · New features in R-INLA (April 2015) · New paper in applied fisheries ecolgy using INLA/ 
    RPubs - DEM 7903 Bayesian Regression using the INLA
    Below, I show examples of using INLA to fit Bayesian regression models for data from US counties. One example will be a relatively small data set from Texas, while the other example will be all US counties. The US county example basically emulates the paper by Sparks et al 2012. library(maptools)
    Spatial and Spatio-temporal Bayesian Models with R - INLA - Wiley
    4.9 How INLA works: step by step example 127 5 Bayesian regression and hierarchical models 139 5.1 Linear Regression 139 5.2 Nonlinear regression: random walk 145 5.3 Generalized Linear Models 150 5.4 Hierarchical Models 159 5.5 Prediction 176 5.6 Model Checking and Selection 179 6 SpatialModeling 189
    SPDE-tutorial - The R-INLA project
    Minicurso: Advances and Challenges in Space-time Modelling (17-18 June 2013 , Lisbon) · Model criticism and conflict diagnostics using R-INLA · N-Mixture models · NCSE Summer Workshop 2015: "Flexible spatial (and spatio-temporal) modelling using the SPDE approach “ · New book: "Bayesian RegressionModeling 
    Case studies and code from papers - The R-INLA project
    Minicurso: Advances and Challenges in Space-time Modelling (17-18 June 2013 , Lisbon) · Model criticism and conflict diagnostics using R-INLA · N-Mixture models · NCSE Summer Workshop 2015: "Flexible spatial (and spatio-temporal) modelling using the SPDE approach “ · New book: "Bayesian RegressionModeling