geoCount: An R Package for the Analysis of Geostatistical Count Data
Liang Jing and
Victor De Oliveira
Journal of Statistical Software, 2015, vol. 063, issue i11
Abstract:
We describe the R package geoCount for the analysis of geostatistical count data. The package performs Bayesian analysis for the Poisson-lognormal and binomial-logitnormal spatial models, which are subclasses of the class of generalized linear spatial models proposed by Diggle, Tawn, and Moyeed (1998). The package implements the computational intensive tasks in C++ using an R/C++ interface, and has parallel computation capabilities to speed up the computations. geoCount also implements group updating, Langevin- Hastings algorithms and a data-based parameterization, algorithmic approaches proposed by Christensen, Roberts, and Sköld (2006) to improve the efficiency of the Markov chain Monte Carlo algorithms. In addition, the package includes functions for simulation and visualization, as well as three geostatistical count datasets taken from the literature. One of those is used to illustrate the package capabilities. Finally, we provide a side-by-side comparison between geoCount and the R packages geoRglm and INLA.
Date: 2015-02-10
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v063i11/v63i11.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... ount_1.150120.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v063i11/v63i11.R
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:063:i11
DOI: 10.18637/jss.v063.i11
Access Statistics for this article
Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis
More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().