GeoModels: an R Package for Geostatistical Gaussian and non Gaussian Data Analysis

Welcome to GeoModels

The GeoModels package provides a set of procedures for simulation, estimation and prediction of spatio-temporal random fields.

The main features of the package are:

Tutorials and Examples

Spatial Data

Distribution Description Link
Weibull Analysis of positive spatial data using Weibull random fields Link
Skew-Gaussian Analysis of asymmetric spatial data using skew-Gaussian random fields Link
Gaussian Analysis of global spatial data on the planet Earth using Gaussian random fields Link

SpatioTemporal Data

Distribution Description Link
Gaussian Analysis of (large) spatio-temporal data using Gaussian random fields Link

Resources and Download

Latest binaries and sources for GeoModels are availables from GitHub repository:

Installation Instructions

We currently are loaded in Github only. This means that for GeoModels installation you will need to previously install devtools package if you do not have it installed yet:


devtools lets you install packages from github since they need to be installed from source code.

We have developed two GeoModels version, one standard version and one that uses the OpenCL framework for parallel computing. The standard version can be installed in any operating system: Windows, OSX and Linux,


and you are good to go.

The OpenCL GeoModels version is currently supported for OSX only. It is installed with this code:



Associated publications:

Package Citation

Once you have installed GeoModels, you can have a BibTex citation with citation("GeoModels") and get:

To cite package ‘GeoModels’ in publications use:
Moreno Bevilacqua and Víctor Morales-Oñate (2018). GeoModels: A Package for Geostatistical Gaussian and non Gaussian Data Analysis.
R package version 1.0.3-4.

A BibTeX entry for LaTeX users is
title = {GeoModels: A Package for Geostatistical Gaussian and non Gaussian Data Analysis},
author = {Bevilacqua, M. and Morales-O{\~n}ate, V.},
year = {2018},
note = {R package version 1.0.3-4},
url = {},

About the authors

Moreno Bevilacqua


Moreno Bevilacqua is an Associate Professor at the Statistics Department of University of Valparaiso from August 2012. He has carried out research as: a post-doc at the Department of Statistics, University Ca' Foscari of Venice from May 2008 to December 2010, a research fellow at the University of Bergamo from January 2011 to July 2012.
He received his PhD in Statistics in 2008 and his Degree in Statistics in 2001 from the University of Padua. His main research interests concern theory, methodology and applications in multivariate spatio-temporal statistics.

Personal site

Víctor Morales-Oñate


Víctor is a PhD candidate of the statistics programme at the University of Valparaíso. His main research interests concern computational spatial (temporal) geostatistics applications.
Other interests include cuantitative economy, fraud detection models, clustering and philosophy, particularly, Bertrand Russell's political ideas.

Personal site