inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Facilitates spatial and general latent Gaussian modelling using integrated nested Laplace approximation via the INLA package (<https://www.r-inla.org>). Additionally, extends the GAM-like model class to more general nonlinear predictor expressions, and implements a log Gaussian Cox process likelihood for modelling univariate and spatial point processes based on ecological survey data. Model components are specified with general inputs and mapping methods to the latent variables, and the predictors are specified via general R expressions, with separate expressions for each observation likelihood model in multi-likelihood models. A prediction method based on fast Monte Carlo sampling allows posterior prediction of general expressions of the latent variables. Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019) <doi:10.1111/2041-210X.13168>.

Version: 2.15.0
Depends: methods, R (≥ 4.1.0)
Imports: dplyr, fmesher (≥ 0.7.0), generics, glue, lifecycle, MatrixModels, Matrix, Rcpp, rlang, sf, stats, tibble, utils, withr
LinkingTo: Rcpp
Suggests: covr, ggplot2, graphics, INLA (≥ 23.01.31), knitr, maps, mgcv, patchwork, raster, RColorBrewer, rgl, rmarkdown, scales, scoringRules, shiny, sn, sp (≥ 2.1), spatstat.geom, spatstat.data, sphereplot, splancs, terra (≥ 1.7-66), tidyterra, testthat (≥ 3.2.0), tidyr, DiagrammeR, doclisting
Enhances: stars
Published: 2026-07-28
DOI: 10.32614/CRAN.package.inlabru
Author: Finn Lindgren ORCID iD [aut, cre, cph] (Finn Lindgren continued development of the main code), Fabian E. Bachl [aut, cph] (Fabian Bachl wrote the main code), David L. Borchers [ctb, dtc, cph] (David Borchers wrote code for Gorilla data import and sampling, multiplot tool), Daniel Simpson [ctb, cph] (Daniel Simpson wrote the basic LGCP sampling method), Lindesay Scott-Howard [ctb, dtc, cph] (Lindesay Scott-Howard provided MRSea data import code), Andy Seaton [ctb] (Andy Seaton provided testing, bugfixes, and vignettes), Man Ho Suen ORCID iD [ctb, cph] (Man Ho Suen contributed features for aggregated responses and vignette updates), Pierre Roudier [ctb, cph] (Pierre Roudier contributed general quantile summaries), Tim Meehan [ctb, cph] (Tim Meehan contributed the SVC vignette and robins data), Niharika Reddy Peddinenikalva [ctb, cph] (Niharika Peddinenikalva contributed the LGCP residuals vignette), Dmytro Perepolkin [ctb, cph] (Dmytro Perepolkin contributed the ZIP/ZAP vignette), Novica Nakov ORCID iD [ctb], Hans Montcho ORCID iD [ctb, cph] (Hans Montcho contributed features for joint cross validation)
Maintainer: Finn Lindgren <finn.lindgren at gmail.com>
BugReports: https://github.com/inlabru-org/inlabru/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.inlabru.org, https://inlabru-org.github.io/inlabru/, https://github.com/inlabru-org/inlabru
NeedsCompilation: yes
Additional_repositories: https://inla.r-inla-download.org/R/testing
Citation: inlabru citation info
Materials: README, NEWS
In views: MixedModels
CRAN checks: inlabru results

Documentation:

Reference manual: inlabru.html , inlabru.pdf
Vignettes: Articles list (source, R code)
Devel: Customised model components with the bru_mapper system (source, R code)
Classes and methods (source, R code)
Defining model components (source, R code)
Nonlinear model approximation (source, R code)
Iterative linearised INLA method (source, R code)
Prediction scores (source, R code)

Downloads:

Package source: inlabru_2.15.0.tar.gz
Windows binaries: r-devel: inlabru_2.14.1.zip, r-release: inlabru_2.14.1.zip, r-oldrel: inlabru_2.14.1.zip
macOS binaries: r-release (arm64): inlabru_2.15.0.tgz, r-oldrel (arm64): inlabru_2.15.0.tgz, r-release (x86_64): inlabru_2.14.1.tgz, r-oldrel (x86_64): inlabru_2.14.1.tgz
Old sources: inlabru archive

Reverse dependencies:

Reverse depends: PointedSDMs
Reverse imports: bmstdr, INLAspacetime, intSDM
Reverse suggests: clustTMB, excursions, MetricGraph, ngme2, rSPDE

Linking:

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