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geoCount (version 1.150120)

Analysis and Modeling for Geostatistical Count Data

Description

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.

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Version

Install

install.packages('geoCount')

Monthly Downloads

18

Version

1.150120

License

GPL (>= 2)

Maintainer

Liang Jing

Last Published

January 27th, 2015

Functions in geoCount (1.150120)

Rongelap

Data Set of Rongelap Island
e2dist

Calculate Distances between Transformed Residuals and Standard Normal
locUloc

Calculate the Distance Matrix Between Observed and Predicting Locations
rhoPowerExp

Powered Exponential Correlation Function
plot_pRPS

Plot Observed vs. Reference Diagnostic Statistics
runMCMC_

Internal Function for Robust MCMC Algorithms
loc2U_R

Calculate the Distance Matrix among Given Locations
locUloc_R

Calculate the Distance Matrix Between Observed and Predicting Locations
BMCT

Perform Bayesian Model Checking
Weed

Weed Data
TexasCounty.population

Data Set of Texas County Population
plotACF

Auto-correlation Plot for Latent Variables
tranR

Calculate Transformed Residuals for Observed Data
helloWorld

Hello
Earthquakes

Data Set of Earthquakes
TexasCounty.boundary

Data Set of Texas County Boundries
U2Z

Convert Distance Matrix to Correlation Matrix
loc2U

Calculate the Distance Matrix among Given Locations
plot_etran

Plot Transformed Residuals
cdfU

Approximate the CDF Value from Reference Samples
cutChain

Modify Markov Chains with Burn-in and Thining
unifLoc

Scale Locations into A Unit Square
baseline.dist

Generate Distance Samples to Build Baseline Distribution
findMode

Estimate Mode of the Posterior Samples
pRPS

Calculate P-value and RPS
simData

Simulate Data Set from Generalized Linear Spatial Model on Given Locations
repYpost

Generate Replicated Data with Posterior Samples of Latent Variables
runMCMCpartialPois_

Internal Function for Robust MCMC Algorithms with Partial Posterior Sampling
locSquad

Simulate Squared Locations
runMCMC

Perform Robust MCMC Algorithms for GLSM
mixChain

Mix Parallel Markov Chains
rhoMatern

Matern Correlation Function
d.base

Data Set of Baseline Samples
runMCMC.sf

Perform Robust MCMC Algorithms for GLSM in Parallel
repYeb

Generate Replicated Data with Estimated Parameters
rhoSph

Spherical Correlation Function
plotTexas

Plot Texas Counties
MCMCinput

Settings for the MCMC Algorithm
locGrid

Simulate Locations on Grid
TexasCounty.center

Data Set of Texas County Centers
Rhizoc

Rhizoc Data
plotData

Plot Geostatistical Data
plot_baseline

Plot Baseline Samples
locCircle

Simulate Circlular Locations
predY

Predict for Unsampled Locations
pOne

Calculate One-side P-value