|Illustrative session||Download||License and Citing geoR|
|geoRglm||R and S-Plus||geoR resources|
Click for an illustrative session with some of the capabilities of the package.
This document is also available as a vignette. The vignettes files are currently not distributed with the package but are available here:
Please note that as free package, geoR is supplied without any warranty.
Series: Springer Series in Statistics
Diggle, Peter J. & Ribeiro Jr, Paulo Justiniano
2006, X, 230 p., Hardcover
The book webpage
We remind that in order to visualise html help files Windows users should also type options(helphtml=TRUE) before help.start(). This is not necessary for other operating systems.
The publications listed here illustrate the usage and some of the capabilities of geoR. The geostatistical analysis and graphics were performed using the package resources.
Please note that several changes have been
made in the software since the release of the above
document, which nevertheless remains valid as an introductory guide to the
The version currently available is already an updated version of the original document and might be further updated to reflect changes in the package.
A package called geoRglm to fit non-Gaussian geostatistical data using generalised spatial linear models models is now available thanks to a work lead by Ole Christensen, Inst. for Genetik og Bioteknologi, Aarhus Universitet.
Our development platform for geoR
is R running on a Linux system.
Versions for Windows© and Macintosh are also available.
Versions for S-PLUS (library geoS) are no longer maintained.
For more details about statistical analysis and programming
Venables & Ripley (1999) and Venables & Ripley (2000).
For a extensive list of publications related to R and S-PLUS see
the R publications list.
R resources for spatial statistics the CRAN spatial task view which includes a comented list of other R packages for geostatistical and spatial statistical data analysis, as well as other useful resources for spatial statistics.
geoR's development has benefited from the usage/bug report,
contributions and comments from several users.
We thank them all for their valuable input.
Remaining bugs are the authors' sole responsibility.
Paulo Justiniano Ribeiro Jr. () is a Professor at LEG (Laboratório de Estatística e Geoinformação), Department of Statistics, Universidade Federal do Paraná, Brasil.
Peter J. Diggle is Professor of Statistics, Lancaster University, UK.