install.packages("INLA",repos=c(getOption("repos"),INLA="https://inla.r-inla-download.org/R/stable"), dep=TRUE)Bayesian modeling with INLA
INLA
Workshop web address: https://d-rug.github.io/workshop_inla
INLA is an acronym for Integrated Nested Laplace Approximations. That’s a mouthful, so just know that it is an extremely fast way of estimating Bayesian regression models that uses approximations to get the parameter estimates, rather than sampling like in MCMC software (e.g. Stan, BUGS, JAGS).
The main advantage is that INLA is incredibly fast, which is especialy noticeable for complex models that are slow to sample (e.g., spatial regression models). That’s why most INLA examples are spatial regression models, but INLA is useful whenever there is a latent Gaussian layer in your model (e.g., random effects).
Install INLA
Follow the instructions here: https://www.r-inla.org/download-install
Or, try this in R (copied from the link):