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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Bayesian Latent Gaussian Modelling using INLA and Extensions</dc:title>
  <dc:title>R package inlabru version 2.15.0</dc:title>
  <dc:subject>CRAN Task View: MixedModels (https://CRAN.R-project.org/view=MixedModels)</dc:subject>
  <dc:description>Facilitates spatial and general latent Gaussian modelling using
  integrated nested Laplace approximation via the INLA package (&lt;https://www.r-inla.org&gt;).
  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)
  &lt;doi:10.1111/2041-210X.13168&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: methods, R (&gt;= 4.1.0)</dc:relation>
  <dc:relation>Imports: dplyr, fmesher (&gt;= 0.7.0), generics, glue, lifecycle,
MatrixModels, Matrix, Rcpp, rlang, sf, stats, tibble, utils,
withr</dc:relation>
  <dc:relation>LinkingTo: Rcpp</dc:relation>
  <dc:relation>Suggests: covr, ggplot2, graphics, INLA (&gt;= 23.01.31), knitr, maps,
mgcv, patchwork, raster, RColorBrewer, rgl, rmarkdown, scales,
scoringRules, shiny, sn, sp (&gt;= 2.1), spatstat.geom,
spatstat.data, sphereplot, splancs, terra (&gt;= 1.7-66),
tidyterra, testthat (&gt;= 3.2.0), tidyr, DiagrammeR, doclisting</dc:relation>
  <dc:relation>Enhances: stars</dc:relation>
  <dc:creator>Finn Lindgren &lt;finn.lindgren@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Finn Lindgren [aut, cre, cph] (ORCID:
    &lt;https://orcid.org/0000-0002-5833-2011&gt;, 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 [ctb, cph] (ORCID: &lt;https://orcid.org/0009-0003-2281-0776&gt;,
    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 [ctb] (ORCID: &lt;https://orcid.org/0009-0005-7773-7718&gt;),
  Hans Montcho [ctb, cph] (ORCID:
    &lt;https://orcid.org/0000-0003-2510-2102&gt;, Hans Montcho contributed
    features for joint cross validation)</dc:contributor>
  <dc:rights>GPL (&gt;= 2)</dc:rights>
  <dc:date>2026-07-28</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=inlabru</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.inlabru</dc:identifier>
</oai_dc:dc>
