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geoCount: An R Package for the Analysis of Geostatistical Count Data
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Abstract
En 中文
We describe the R package geo Count 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, LangevinHastings algorithms and a data-based parameterization, algorithmic approaches proposed by Christensen, Roberts, and Skold (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
Keywords:
Bayesian inference
geostatistics
hierarchical models
kriging
Markov chain Monte Carlo
parallel computing
Journal
IF:
8.1
Papers:
616
Citations:
4.6W
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