Facilitates spatial modeling using integrated nested Laplace approximation via the INLA package (<http://www.r-inla.org>). 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: | 2.1.3 |
| Depends: | R (≥ 3.3), sp, stats, methods, ggplot2 |
| Imports: | rgdal, rgeos, utils |
| Suggests: | testthat, ggmap, rgl, sphereplot, raster, Matrix, dplyr, maptools, mgcv, shiny, spatstat, spatstat.data, RColorBrewer, graphics, INLA |
| Published: | 2018-02-11 |
| Author: | Fabian E. Bachl (main code), Finn Lindgren (SPDE posterior plotting), David L. Borchers (Gorilla data import and sampling, multiplot tool), Daniel Simpson (basic LGCP sampling method), Lindesay Scott-Hayward (MRSea data import) |
| Maintainer: | Fabian E. Bachl <bachlfab at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://www.inlabru.org, |
| NeedsCompilation: | no |
| CRAN checks: | inlabru results |
| Reference manual: | inlabru.pdf |
| Package source: | inlabru_2.1.3.tar.gz |
| Windows binaries: | r-devel: inlabru_2.1.3.zip, r-release: inlabru_2.1.3.zip, r-oldrel: inlabru_2.1.3.zip |
| OS X El Capitan binaries: | r-release: inlabru_2.1.3.tgz |
| OS X Mavericks binaries: | r-oldrel: not available |
| Old sources: | inlabru archive |
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