GeoModels: Procedures for Gaussian and Non Gaussian Geostatistical (Large) Data Analysis

Functions for Gaussian and Non Gaussian (bivariate) spatial and spatio-temporal data analysis are provided for a) (fast) simulation of random fields, b) inference for random fields using standard likelihood and a likelihood approximation method called weighted composite likelihood based on pairs and b) prediction using (local) best linear unbiased prediction. Weighted composite likelihood can be very efficient for estimating massive datasets. Both regression and spatial (temporal) dependence analysis can be jointly performed. Flexible covariance models for spatial and spatial-temporal data on Euclidean domains and spheres are provided. There are also many useful functions for plotting and performing diagnostic analysis. Different non Gaussian random fields can be considered in the analysis. Among them, random fields with marginal distributions such as Skew-Gaussian, Student-t, Tukey-h, Sin-Arcsin, Two-piece, Weibull, Gamma, Log-Gaussian, Binomial, Negative Binomial and Poisson. See the URL for the papers associated with this package, as for instance, Bevilacqua and Gaetan (2015) <doi:10.1007/s11222-014-9460-6>, Bevilacqua et al. (2016) <doi:10.1007/s13253-016-0256-3>, Vallejos et al. (2020) <doi:10.1007/978-3-030-56681-4>, Bevilacqua et. al (2020) <doi:10.1002/env.2632>, Bevilacqua et. al (2021) <doi:10.1111/sjos.12447>, Bevilacqua et al. (2022) <doi:10.1016/j.jmva.2022.104949>, Morales-Navarrete et al. (2023) <doi:10.1080/01621459.2022.2140053>, and a large class of examples and tutorials.

Version: 2.0.3
Depends: R (≥ 4.1.0), fields, mapproj, shape, codetools
Imports: methods, spam, scatterplot3d, dotCall64, FastGP, plotrix, pracma, pbivnorm, zipfR, sn, sp, lamW, nabor, hypergeo, VGAM, data.table, foreach, future, doFuture, progressr
Suggests: actuar, GoFKernel, optimParallel, numDeriv
Published: 2024-06-07
DOI: 10.32614/CRAN.package.GeoModels
Author: Moreno Bevilacqua ORCID iD [aut, cre], Víctor Morales-Oñate ORCID iD [aut], Christian Caamaño-Carrillo ORCID iD [aut]
Maintainer: Moreno Bevilacqua <moreno.bevilacqua89 at gmail.com>
BugReports: https://github.com/vmoprojs/GeoModels/issues
License: GPL (≥ 3)
URL: https://vmoprojs.github.io/GeoModels-page/
NeedsCompilation: yes
CRAN checks: GeoModels results

Documentation:

Reference manual: GeoModels.pdf

Downloads:

Package source: GeoModels_2.0.3.tar.gz
Windows binaries: r-devel: GeoModels_2.0.3.zip, r-release: GeoModels_2.0.2.zip, r-oldrel: GeoModels_2.0.3.zip
macOS binaries: r-release (arm64): GeoModels_2.0.3.tgz, r-oldrel (arm64): GeoModels_2.0.3.tgz, r-release (x86_64): GeoModels_2.0.3.tgz, r-oldrel (x86_64): GeoModels_2.0.3.tgz
Old sources: GeoModels archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=GeoModels to link to this page.