inlabru: Spatial Inference using Integrated Nested Laplace Approximation

Facilitates spatial modeling using integrated nested Laplace approximation via the INLA package (<>). Additionally, implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. See Yuan Yuan, Fabian E. Bachl, Finn Lindgren, David L. Borchers, Janine B. Illian, Stephen T. Buckland, Havard Rue, Tim Gerrodette (2017), <arXiv:1604.06013>.

Version: 2.1.9
Depends: R (≥ 3.3), sp, stats, methods, ggplot2
Imports: rgdal, rgeos, utils, Matrix
Suggests: testthat, ggmap, rgl, sphereplot, raster, dplyr, maptools, mgcv, shiny, spatstat,, RColorBrewer, graphics, INLA, knitr, rmarkdown
Published: 2018-07-24
Author: Fabian E. Bachl [aut, cre] (Fabian Bachl wrote the main code), Finn Lindgren ORCID iD [aut] (Finn Lindgren wrote code for SPDE posterior plotting, and continued development of the main code), David L. Borchers [ctb] (David Borchers wrote code for Gorilla data import and sampling, multiplot tool), Daniel Simpson [ctb] (Daniel Simpson wrote the basic LGCP sampling method), Lindesay Scott-Howard [ctb] (Lindesay Scott-Howard provied MRSea data import code)
Maintainer: Fabian E. Bachl <bachlfab at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README NEWS
CRAN checks: inlabru results


Reference manual: inlabru.pdf
Package source: inlabru_2.1.9.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: inlabru_2.1.9.tgz, r-oldrel: inlabru_2.1.9.tgz
Old sources: inlabru archive


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