geostatsp: Geostatistical Modelling with Likelihood and Bayes

Geostatistical modelling facilities using 'SpatRaster' and 'SpatVector' objects are provided. Non-Gaussian models are fit using 'INLA', and Gaussian geostatistical models use Maximum Likelihood Estimation. For details see Brown (2015) <doi:10.18637/jss.v063.i12>. The 'RandomFields' package is available at <https://www.wim.uni-mannheim.de/schlather/publications/software>.

Version: 2.0.6
Depends: Matrix, terra, R (≥ 3.5.0)
Imports: abind, numDeriv, methods, stats
LinkingTo: Matrix (≥ 1.6-2)
Suggests: RandomFields, parallel, mapmisc, ellipse, pracma, knitr
Enhances: INLA, diseasemapping, geoR, mvtnorm
Published: 2024-02-20
Author: Patrick Brown [aut, cre, cph]
Maintainer: Patrick Brown <patrick.brown at utoronto.ca>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
Additional_repositories: https://inla.r-inla-download.org/R/testing
Citation: geostatsp citation info
CRAN checks: geostatsp results

Documentation:

Reference manual: geostatsp.pdf
Vignettes: Various GLGM examples
LGCP with PC priors

Downloads:

Package source: geostatsp_2.0.6.tar.gz
Windows binaries: r-devel: geostatsp_2.0.3.zip, r-release: geostatsp_2.0.6.zip, r-oldrel: geostatsp_2.0.6.zip
macOS binaries: r-release (arm64): geostatsp_2.0.6.tgz, r-oldrel (arm64): geostatsp_2.0.6.tgz, r-release (x86_64): geostatsp_2.0.6.tgz
Old sources: geostatsp archive

Linking:

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