Package: inlabru
Type: Package
Title: Spatial Inference using Integrated Nested Laplace Approximation
Version: 2.1.3
Date: 2018-02-10
Author: Fabian E. Bachl <bachlfab@gmail.com> (main code), 
        Finn Lindgren <Finn.Lindgren@ed.ac.uk> (SPDE posterior plotting),
        David L. Borchers <dlb@st-andrews.ac.uk> (Gorilla data import and sampling, multiplot tool), 
        Daniel Simpson <dp.simpson@gmail.com> (basic LGCP sampling method),
        Lindesay Scott-Hayward <lass@@st-andrews.ac.uk> (MRSea data import)
Maintainer: Fabian E. Bachl <bachlfab@gmail.com>
URL: http://www.inlabru.org,
Description: 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>.
License: GPL (>= 2)
Imports: rgdal, rgeos, utils
Suggests: testthat, ggmap, rgl, sphereplot, raster, Matrix, dplyr,
        maptools, mgcv, shiny, spatstat, spatstat.data, RColorBrewer,
        graphics, INLA,
Depends: R (>= 3.3), sp, stats, methods, ggplot2,
Additional_repositories: https://www.math.ntnu.no/inla/R/testing
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-02-10 18:42:47 UTC; fbachl
Repository: CRAN
Date/Publication: 2018-02-11 14:26:23 UTC
Built: R 3.3.3; ; 2018-04-22 17:07:47 UTC; windows
