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: | 2.5.2 |
| Depends: | methods, R (≥ 3.5), sp (≥ 1.4-5), stats |
| Imports: | MatrixModels, magrittr, Matrix, plyr, rgdal (≥ 1.5.8), rgeos, rlang, utils, withr |
| Suggests: | covr, dplyr, ggmap, ggplot2, ggpolypath, graphics, INLA (≥ 21.08.31), knitr, maptools, mgcv, patchwork, raster, RColorBrewer, rgl, rmarkdown, shiny, sn, spatstat.geom, spatstat.core, spatstat.data, spatstat (≥ 2.0-0), sphereplot, testthat |
| Published: | 2022-03-30 |
| 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 and bugfixes),
Suen Man Ho [ctb, cph] (Man Ho Suen contributed features for aggregated
responses) |
| 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/ |
| NeedsCompilation: | no |
| Additional_repositories: | https://inla.r-inla-download.org/R/testing |
| Citation: | inlabru citation info |
| Materials: | README NEWS |
| CRAN checks: | inlabru results |
Documentation:
| Reference manual: | inlabru.pdf |
| Vignettes: |
Nonlinear model approximation Iterative INLA method Examples on the inlabru website |
Downloads:
| Package source: | inlabru_2.5.2.tar.gz |
| Windows binaries: | r-devel: inlabru_2.5.2.zip, r-release: inlabru_2.5.2.zip, r-oldrel: inlabru_2.5.2.zip |
| macOS binaries: | r-release (arm64): inlabru_2.5.2.tgz, r-oldrel (arm64): inlabru_2.5.2.tgz, r-release (x86_64): inlabru_2.5.2.tgz, r-oldrel (x86_64): inlabru_2.5.2.tgz |
| Old sources: | inlabru archive |
Reverse dependencies:
| Reverse depends: | PointedSDMs |
| Reverse imports: | bmstdr |
Linking:
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