• Version 20.11.16-3 is out

This is an important release; the instabilities experienced with the PARDISO library has been fixed and nested parallelism now works out of the box (Linux & Mac). This concludes the huge ammount of work started four months ago. There is speedup improvement especially for models with many constraints. `plot' now works with argument 'cex' so, f.ex, labels can be made larger easily. See news(package="INLA") for details .

  • Windows ``builder'' wanted

Our knowledge in Windows is limited, meaning that the builds provided in the package works but sometimes with limited support. Like, the PARDISO library, Intel MKL support, jemalloc, is not there for this reason. If someone would like to help us out here, it would be great! The task is essentially to provide a better Windows build of the inla-program for each release, which can be downloaded using similar functionality as `inla.binary.install()', The code is mainly C, with some C++ and Fortran. If you're interested, please email me at .

  • 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.

  • 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.

  • 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.


  • Stability issues for Ubuntu 18.04 and 20.04, 2 Sep 2020

In the most recent testing version(s) there is a stability issue for Ubuntu when running with nested parallelism and the PARDISO library. It seems like the builds from CentOS 7 & 8 are much more stable.

Is this becomes an issue, please do 'inla.binary.install()' and try the CentOS7 (Ubuntu 18) or CentOS8 (Ubuntu 20) instead. We're looking into the issue.

  • macOS 10.15 Catalina, 13 Jul 2020

is now used to build the INLA package for Mac. Let us know if this causes any issues.

  • Finally, R-4.0, 9 Jul 2020

The testing version of today, Version_20.07.09, is built on R-4.0.2. This also includes all alternative binary Linux builds, but they are less affected.

There is currently no stable version built with R-4.0, but the testing one can be used instead. If there are any issues, please let us know.

  • Multivariate spatial models for lattice data with INLA, 7 May 2020

A paper on fitting several multivariate spatial models for lattice data with INLA has been published in the arXiv by F. Palmí-Perales et al. The associated R package INLAMSM is available from GitHub and CRAN. Models have been implemented using the rgeneric framework and they include a multivariate intrinsic CAR mode, multivariate proper CAR model and the M-model.