R-INLA is a package in R that do approximate Bayesian inference for Latent Gaussian Models. This site is dedicated to that package and methodological developments that goes along with it.

The integrated nested Laplace approximation (INLA) is a method for approximate Bayesian inference. In the last years it has established itself as an alternative to other methods such as …

To install the INLA-package in R, you have to manually add the r-inla repository as we are not on CRAN.

Here is a list of worked out examples and tutorials using R-INLA: INLA course on discrete data (Video 1: Intro - Video 2: Hands-on ) , Luigi &Thomas, at Spatial Data Science conference …

INLA has some functions to work with graphs, and here is a short summary. inla.read.graph() and inla.write.graph(), read and write graphs using any of the graph specifications above. You can …

Update INLA... To Make it Faster!

Spatial and Spatio-Temporal models with R-INLA, Blangiardo, Cameletti, Baio, and Rue , 2012. The data-sets are found here and the R-code is found here , for the first two examples. For …

Selected List of Latent Models, Likelihoods, Priors and Vignettes found in INLA:

It provides detailed explanations on how to fit and interpret Bayesian spatial models using the integrated nested Laplace approximation (INLA) and stochastic partial differential equation …

2010年7月21日 · 'A new version of the R-INLA package, 21.06.11, is out with some nice new features. Native build for R-4.1 and Mac M1 processor, included ported PARDISO library. For …