inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Facilitates spatial and general latent Gaussian modeling 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 modeling 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:	2.12.0
Depends:	fmesher (≥ 0.2.0), methods, R (≥ 3.6), stats
Imports:	dplyr, lifecycle, magrittr, MatrixModels, Matrix, plyr, rlang, sf, tibble, utils, withr
Suggests:	covr, ggplot2, graphics, INLA (≥ 23.01.31), knitr, maps, mgcv, patchwork, raster, RColorBrewer, rgl, rmarkdown, scales, shiny, sn, sp (≥ 2.1), spatstat.geom, spatstat.data, sphereplot, splancs, terra, tidyterra, testthat, tidyr, DiagrammeR
Enhances:	stars
Published:	2024-11-21
DOI:	10.32614/CRAN.package.inlabru
Author:	Finn Lindgren [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), Seaton Andy [ctb] (Andy Seaton provided testing, bugfixes, and vignettes), Suen Man Ho [ctb, cph] (Man Ho Suen contributed features for aggregated responses and vignette updates), Roudier Pierre [ctb, cph] (Pierre Roudier contributed general quantile summaries), Meehan Tim [ctb, cph] (Tim Meehan contributed the SVC vignette and robins data), Reddy Peddinenikalva Niharika [ctb, cph] (Niharika Peddinenikalva contributed the LGCP residuals vignette), Perepolkin Dmytro [ctb, cph] (Dmytro Perepolkin contributed the ZIP/ZAP vignette)
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:	no
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.pdf
Vignettes:	Articles list (source, R code) Devel: Customised model components with the bru_mapper system (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_2.12.0.tar.gz
Windows binaries:	r-devel: inlabru_2.12.0.zip, r-release: inlabru_2.12.0.zip, r-oldrel: inlabru_2.12.0.zip
macOS binaries:	r-release (arm64): inlabru_2.12.0.tgz, r-oldrel (arm64): inlabru_2.12.0.tgz, r-release (x86_64): inlabru_2.12.0.tgz, r-oldrel (x86_64): inlabru_2.12.0.tgz
Old sources:	inlabru archive

Reverse dependencies:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=inlabru to link to this page.