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GeoModels
View on CRAN: Click
here
Download and install GeoModels package within the R console
Install from CRAN:
install.packages("GeoModels")
Install from Github:
library("remotes")
install_github("cran/GeoModels")
Install by package version:
library("remotes")
install_version("GeoModels", "2.0.1")
Attach the package and use:
library("GeoModels")
Maintained by
Moreno Bevilacqua
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-25
Latest Update: 2023-08-29
Description:
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) , Bevilacqua et al. (2016) , Vallejos et al. (2020) , Bevilacqua et. al (2020) , Bevilacqua et. al (2021) , Bevilacqua et al. (2022) , Morales-Navarrete et al. (2023) , and a large class of examples and tutorials.
How to cite:
Moreno Bevilacqua (2022). GeoModels: Procedures for Gaussian and Non Gaussian Geostatistical (Large) Data Analysis. R package version 2.0.1, https://cran.r-project.org/web/packages/GeoModels
Previous versions and publish date:
1.0.0 (2022-05-25 09:40), 1.0.1 (2022-06-05 16:10), 1.0.2 (2022-09-04 16:30), 1.0.3 (2022-10-23 12:27), 1.0.4 (2022-11-30 09:10), 1.0.5 (2022-12-05 09:32), 1.0.6 (2023-01-07 14:50), 1.0.7 (2023-03-14 14:50), 1.0.8 (2023-05-30 16:40), 1.0.9 (2023-08-07 23:00), 1.1.0 (2023-08-16 11:02), 1.1.1 (2023-08-29 10:30), 1.1.2 (2023-09-08 22:40), 1.1.3 (2023-09-23 14:30), 1.1.4 (2023-10-21 15:00), 1.1.5 (2023-11-14 10:43), 1.1.6 (2024-02-06 18:40), 1.1.7 (2024-02-19 08:50), 1.1.8 (2024-03-13 11:20), 1.1.9 (2024-03-21 09:30), 2.0.0 (2024-04-10 00:20), 2.0.1 (2024-04-11 13:40)
Other packages that cited GeoModels R package
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Other R packages that GeoModels depends,
imports, suggests or enhances
Functions, R codes and Examples using
the GeoModels R package
Some associated functions: Anomalies . CheckBiv . CheckDistance . CheckST . CheckSph . CkCorrModel . CkInput . CkLikelihood . CkModel . CkType . CkVarType . CompIndLik2 . CompLik . CompLik2 . CorrParam . CorrelationPar . GeoAniso . GeoCV . GeoCorrFct . GeoCorrFct_Cop . GeoCovDisplay . GeoCovariogram . GeoCovmatrix . GeoFit . GeoFit2 . GeoKrig . GeoKrigloc . GeoNA . GeoNeighIndex . GeoNeighborhood . GeoNosymindices . GeoOutlier . GeoPit . GeoQQ . GeoResiduals . GeoScatterplot . GeoSim . GeoSimCopula . GeoSimapprox . GeoTests . GeoVarestbootstrap . GeoVariogram . GeoWls . Lik . MatDecomp . Matrixfun . NuisParam . Prscores . StartParam . WlsStart . austemp . plot.GeoVariogram . winds.coords . winds .
Some associated R codes: GeoAniso.R . GeoCV.R . GeoCompositeLik2.R . GeoCorrFct_Cop.R . GeoCovDisplay.R . GeoFit2.R . GeoIndCompositeLik2.R . GeoKrigloc.R . GeoNA.R . GeoNeighIndex.R . GeoNeighborhood.R . GeoNosymindices.R . GeoPit.R . GeoQQ.R . GeoScatterplot.R . GeoSimCopula.R . GeoSpoutlier.R . Geovarestbootstrap.R . Full GeoModels package functions and examples
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