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.

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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.


Solving Real-World Problems: A tool developed by Håvard Rue has transformed data analysis, interpretation and communication. It has been applied broadly: from modeling the spread of infectious diseases to mapping fish stocks, 2018.

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