{ "_id": "6ae50829327abcdf86868da7", "Package": "GeoModels", "Version": "2.3.0", "Date": "2026-10-29", "Authors@R": "c(person(\"Moreno\", \"Bevilacqua\", role = c(\"aut\", \"cre\",\"cph\"),\nemail = \"moreno.bevilacqua89@gmail.com\"),\nperson(\"Víctor\", \"Morales-Oñate\", role = \"ctb\"),\nperson(\"Francisco\", \"Cuevas-Pacheco\", role = \"ctb\"),\nperson(\"Christian\", \"Caamaño-Carrillo\", role = \"ctb\"))", "Description": "Functions for Gaussian and Non Gaussian (bivariate)\nspatial and spatio-temporal data analysis are provided for a)\n(fast) simulation of random fields, b) inference for random\nfields using standard likelihood and a likelihood approximation\nmethod called weighted composite likelihood based on pairs and\nb) prediction using (local) best linear unbiased prediction.\nWeighted composite likelihood can be very efficient for\nestimating massive datasets. Both regression and spatial\n(temporal) dependence analysis can be jointly performed.\nFlexible covariance models for spatial and spatial-temporal\ndata on Euclidean domains and spheres are provided. There are\nalso many useful functions for plotting and performing\ndiagnostic analysis. Different non Gaussian random fields can\nbe considered in the analysis. Among them, random fields with\nmarginal distributions such as Skew-Gaussian, Student-t,\nTukey-h, Sin-Arcsin, Two-piece, Weibull, Gamma, Log-Gaussian,\nBinomial, Negative Binomial and Poisson. See the URL for the\npapers associated with this package, as for instance,\nBevilacqua and Gaetan (2015) ,\nBevilacqua et al. (2016) ,\nVallejos et al. (2020) ,\nBevilacqua et. al (2020) , Bevilacqua et.\nal (2021) , Bevilacqua et al. (2022)\n, Morales-Navarrete et al.\n(2023) , and a large class\nof examples and tutorials.", "Title": "Procedures for Gaussian and Non Gaussian Geostatistical (Large)\nData Analysis", "License": "GPL (>= 3)", "Encoding": "UTF-8", "URL": "https://vmoprojs.github.io/GeoModels-page/", "BugReports": "https://github.com/vmoprojs/GeoModels/issues", "NeedsCompilation": "yes", "SystemRequirements": "OpenMP (optional)", "Author": "Moreno Bevilacqua [aut, cre, cph], Víctor Morales-Oñate [ctb],\nFrancisco Cuevas-Pacheco [ctb], Christian Caamaño-Carrillo\n[ctb]", "Maintainer": "Moreno Bevilacqua ", "Packaged": { "Date": "2026-10-30 21:04:46 UTC", "User": "root" }, "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-30 19:31:28 UTC", "RemoteUrl": "https://github.com/cran/GeoModels", "RemoteRef": "HEAD", "RemoteSha": "62c2afe2217de2315217133b15efdd322a249422", "_user": "cran", "_type": "src", "_file": "GeoModels_2.3.0.tar.gz", "_fileid": 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fields.", "topics": [ "GeoKrigloc" ] }, { "page": "GeoKriglocWeights", "title": "Compute validated local Gaussian kriging weights", "topics": [ "GeoKriglocWeights" ] }, { "page": "GeoKrigWeights", "title": "Compute validated Gaussian kriging weights for spatial and spatio-temporal random fields", "topics": [ "GeoKrigWeights" ] }, { "page": "GeoModels-3D", "title": "Three-dimensional spatial coordinates in GeoModels", "topics": [ "GeoModels-3D" ] }, { "page": "GeoModels-spacetime-ordering", "title": "Ordering Conventions for Spatio-temporal Data, Covariates and Predictions", "topics": [ "GeoModels-spacetime-ordering", "spacetime-data-order", "spacetime-ordering" ] }, { "page": "GeoNA", "title": "Deleting NA values (missing values) from a spatial or spatio-temporal dataset.", "topics": [ "GeoNA" ] }, { "page": "GeoNeighborhood", "title": "Spatio (temporal) neighborhood selection for local kriging.", "topics": [ "GeoNeighborhood" ] }, { "page": "GeoNeighbSelect", "title": "Neighborhood Selection for Pairwise Composite Likelihood Estimation", "topics": [ "GeoNeighbSelect" ] }, { "page": "GeoNeighIndex", "title": "Spatial, spatio-temporal, or bivariate nearest-neighbour indices", "topics": [ "GeoNeighIndex" ] }, { "page": "GeoOMP", "title": "Configure Native OpenMP Acceleration", "topics": [ "GeoOMP" ] }, { "page": "GeoOutlier", "title": "Spatial outlier detection", "topics": [ "GeoOutlier" ] }, { "page": "GeoPit", "title": "Probability Integral Transform for Fitted GeoModels Objects", "topics": [ "GeoPit" ] }, { "page": "GeoQQ", "title": "Quantile-quantile plot", "topics": [ "GeoQQ" ] }, { "page": "GeoResiduals", "title": "Compute Residuals from a Fitted GeoModels Model", "topics": [ "GeoResiduals" ] }, { "page": "GeoScatterplot", "title": "Scatterplots of Spatial or Spatio-temporal Pairs and Fitted Bivariate Contours", "topics": [ "GeoScatterplot" ] }, { "page": "GeoScores", "title": "Computation of predictive scores", "topics": [ "GeoScores" ] }, { "page": "GeoSim", 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Support", "topics": [ "GeoTestsupp_space" ] }, { "page": "GeoVarest", "title": "Score-based variance estimation for 'GeoFit' objects", "topics": [ "GeoVarest" ] }, { "page": "GeoVarestbootstrap", "title": "Update a 'GeoFit' object using parametric bootstrap for std error estimation.", "topics": [ "GeoVarestbootstrap" ] }, { "page": "GeoVariogram", "title": "Empirical semivariogram estimation", "topics": [ "GeoVariogram" ] }, { "page": "GeovariogramDir", "title": "Empirical directional semivariogram", "topics": [ "GeoVariogramDir" ] }, { "page": "GeoWls", "title": "WLS of Gaussian random fields", "topics": [ "GeoWLS", "print.GeoWLS" ] }, { "page": "getInvC", "title": "Utility function for kriging computation", "topics": [ "getInvC" ] }, { "page": "Lik", "title": "Optimizes the Log Likelihood", "topics": [ "Lik" ] }, { "page": "madagascartemp", "title": "July Average Temperature of Madagascar", "topics": [ "madagascartemp" ] }, { "page": "MargParam", "title": "Lists the Nuisance 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