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 R-INLA Workshop was a Big Success: An international virtual workshop entitled Introducing R-INLA and its Applications was held by Statistics Study Program on Wednesday, September 30th, 2020 at Airlangga University, Indonesia. Click here.
An INLA-translation of the 2019 homework of Statistical Rethinking: (2nd edition), 23 Sep 2020
Impressive, well done!
Model 'rgeneric' and R-4.0, 29 Sep 2020
There is a minor change in the R-internals in R-4.0 that may make rgeneric models crash if the statement (used in the rgeneric vignette), is used,
if (is.null(theta)) theta = initial()
This statement is used to ensure that 'theta' is always set as some argument do not depend on 'theta'. In R-4.0 you need to change this statement to
if (!length(theta)) theta = initial()
The vignette and examples are updated and will be available in the next build.
Thanks to GV who reported this error.