Title: Bayesian Latent Gaussian Modelling using INLA and Extensions
person("Finn", "Lindgren", email = "finn.lindgren@gmail.com",
"Finn Lindgren continued development of the main code")),
person("Fabian E.", "Bachl", email = "bachlfab@gmail.com",
person("David L.", "Borchers", email = "dlb@st-andrews.ac.uk",
person("Daniel", "Simpson", email = "dp.simpson@gmail.com",
person("Lindesay", "Scott-Howard", email = "lass@st-andrews.ac.uk",
comment = "Lindesay Scott-Howard provided MRSea data import code"),
person("Seaton", "Andy", email = "andy.e.seaton@gmail.com", role = c("ctb"),
comment = "Andy Seaton provided testing and bugfixes")
Description: 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)
Depends: ggplot2, methods, R (>= 3.5), sp (>= 1.4-2), stats
Imports: Matrix, rgdal, rgeos, utils, withr
Suggests: covr, dplyr, ggmap, ggpolypath, graphics, INLA (>= 20.06.18),
knitr, maptools, mgcv, patchwork, raster, RColorBrewer, rgl,
rmarkdown, shiny, sn, spatstat.geom, spatstat.core,
spatstat.data, spatstat (>= 2.0-0), sphereplot, testthat
'model.R' 'nlinla.R' 'plotsample.R' 'prediction.R' 'rgl.R'
'sampling.R' 'shapefile.R' 'spatstat.R' 'spde.R' 'stack.R'
Author: Finn Lindgren [aut, cre, cph] (<https://orcid.org/0000-0002-5833-2011>,
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
Lindesay Scott-Howard [ctb, dtc, cph] (Lindesay Scott-Howard provided
Seaton Andy [ctb] (Andy Seaton provided testing and bugfixes)