About the Package: {geoCount}

This package provides a variety of functions to analyze and model geostatistical count data with generalized linear spatial models, including,
 1) simulate and visualize the data;
 2) posterior sampling with robust MCMC algorithms (in serial or parallel way);
 3) perform prediction for unsampled locations;
 4) conduct Bayesian model checking procedure to evaluate the goodness of fitting;
 5) conduct transformed residual checking procedure.
In the package, seamlessly embedded C++ programs and parallel computing techniques are implemented to speed up the computing processes.
Available for both Linux/Unix and Windows systems.

Package Dependency

• R (>= 2.12.0)
• C++ compiler: for example GNU Compiler Collection (GCC)
• GNU Scientific Library (GSL): a numerical library for C and C++
• LAPACK and BLAS (or ATLAS): libraries for numerical linear algebra operations
• Standard development tools such as make etc.
• R packages
    – Rcpp (>= 0.9.4): provides a C++ API as an extension to the R system
    – RcppArmadillo (>= 0.2.19): integration for “Armadillo” which is a templated C++ linear algebra library
    – {coda}: for Markov chain diagnostics
    – {distrEx}: for calculating Hellinger and Kolmogorov distances between two distributions
    – {reldist}: for calculating the relative density
    – {multicore, snow, snowfall}: for parallel computing

Caution: {Rcpp} and {RcppArmadillo} are required to install
{geoCount}. Other R packages are only required when you use
the corresponding functions in the package.


Manual: [pdf]
Tutorial: "How to Use {geoCount}" [pdf] | Code [R]


Source code: [geoCount_1.130409.tar.gz]
Binary for Windows: for 32-bit R-3.0.0 [geoCount_1.130409.zip]
*See the tutorial for how to install the package.


   • Data and Model Specification
   • Robust MCMC Algorithms
   • Bayesian Model Checking
   • Transformed Residual Checking
   • Techniques for building the package: API between R and C++; parallel computing in R
    *See my dissertation for details.