geoCount: Analysis and Modeling for Geostatistical Count Data

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.

AuthorLiang Jing
Date of publication2013-04-30 13:01:08
MaintainerLiang Jing <>
LicenseGPL (>= 2)

View on R-Forge

Man pages

baseline.dist: Generate Distance Samples to Build Baseline Distribution

baseline.parallel: Generate Distance Samples to Build Baseline Distribution...

BMCT: Perform Bayesian Model Checking

cdfU: Approximate the CDF Value from Reference Samples

cutChain: Modify Markov Chains with Burn-in and Thining

d.base: Data Set of Baseline Samples

e2dist: Calculate Distances between Transformed Residuals and...

Earthquakes: Data Set of Earthquakes

findMode: Estimate Mode of the Posterior Samples

helloWorld: Hello

loc2U: Calculate the Distance Matrix among Given Locations

loc2U_R: Calculate the Distance Matrix among Given Locations

locCircle: Simulate Circlular Locations

locGrid: Simulate Locations on Grid

locSquad: Simulate Squared Locations

locUloc: Calculate the Distance Matrix Between Observed and Predicting...

locUloc_R: Calculate the Distance Matrix Between Observed and Predicting...

MCMCinput: Settings for the MCMC Algorithm

mixChain: Mix Parallel Markov Chains

plotACF: Auto-correlation Plot for Latent Variables

plot_baseline: Plot Baseline Samples

plotData: Plot Geostatistical Data

plotDataBD: Plot Geostatistical Data

plot_etran: Plot Transformed Residuals

plot_pRPS: Plot Observed vs. Reference Diagnostic Statistics

pOne: Calculate One-side P-value

predY: Predict for Unsampled Locations

pRPS: Calculate P-value and RPS

repYeb: Generate Replicated Data with Estimated Parameters

repYpost: Generate Replicated Data with Posterior Samples of Latent...

rhoMatern: Matern Correlation Function

rhoPowerExp: Powered Exponential Correlation Function

Rongelap: Data Set of Rongelap Island

runMCMC: Perform Robust MCMC Algorithms for GLSM

runMCMC.multiChain: Perform Robust MCMC Algorithms for GLSM in Parallel

runMCMC.sf: Perform Robust MCMC Algorithms for GLSM in Parallel

simData: Simulate Data Set from Generalized Linear Spatial Model on...

TexasCounty.boundary: Data Set of Texas County Boundries Data Set of Texas County Centers

TexasCounty.population: Data Set of Texas County Population

tranR: Calculate Transformed Residuals for Observed Data

U2Z: Convert Distance Matrix to Correlation Matrix

unifLoc: Scale Locations into A Unit Square

Weed: Weed Data


baseline.dist Man page
baseline.parallel Man page
BMCT Man page
cdfU Man page
cutChain Man page
d.base Man page
e2dist Man page
Earthquakes Man page
findMode Man page
helloWorld Man page
loc2U Man page
loc2U_R Man page
locCircle Man page
locGrid Man page
locSquad Man page
locUloc Man page
locUloc_R Man page
MCMCinput Man page
mixChain Man page
plotACF Man page
plot_baseline Man page
plotData Man page
plotDataBD Man page
plot_etran Man page
plot_pRPS Man page
pOne Man page
predY Man page
pRPS Man page
repYeb Man page
repYpost Man page
rhoMatern Man page
rhoPowerExp Man page
Rongelap Man page
runMCMC Man page
runMCMC.multiChain Man page
runMCMC.sf Man page
simData Man page
TexasCounty.boundary Man page Man page
TexasCounty.population Man page
tranR Man page
U2Z Man page
unifLoc Man page
Weed Man page

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