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geoRglm (version 0.9-16)

Generalised Linear Spatial Models

Description

Functions for inference in generalised linear spatial models. The posterior and predictive inference is based on Markov chain Monte Carlo methods. Package 'geoRglm' is an extension to the package 'geoR', which must be installed first.

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Version

Install

install.packages('geoRglm')

Monthly Downloads

553

Version

0.9-16

License

GPL (>= 2)

Maintainer

Ole F Christensen

Last Published

March 4th, 2020

Functions in geoRglm (0.9-16)

geoRglm-internal

geoRglm internal functions
binom.krige

Conditional Simulation and Prediction for the Binomial-logit Spatial model
glsm.krige

Prediction for a Generalised Linear Spatial Model
create.mcmc.coda

Create an mcmc object for the CODA package
binom.krige.bayes

Bayesian Posterior Simulation and Prediction for the Binomial Spatial model
hist.glm.krige.bayes

Plots Sample from Posterior Distributions
covariog.model.env

Envelope for Empirical Covariogram for the Poisson-log normal model
glsm.mcmc

Conditional Simulation for a generalised linear spatial model
summary.likGLSM

Summarizes Parameter Estimation Results for Generalised linear Spatial Models
covariog

Empirical Covariogram for a Model with log-link and an Underlying Gaussian Field
geoRglm-defunct

Defunct Functions in the Package geoRglm
asympvar

Asymptotic Variance
output.glm.control

Defines output options
image.glm.krige.bayes

Plots Results of the Predictive Distribution
krige.glm.control

Defines options and model for prediction
mcmc.control

Defines options for the MCMC-algorithm
pois.krige

Conditional Simulation and Prediction for the Poisson Spatial model with a link function from the Box-Cox class
model.glm.control

Defines model options
proflik.glsm

Computes Profile Likelihood for generalised linear spatial models
plot.covariogram

Plot Empirical Covariogram
pois.krige.bayes

Bayesian Posterior Simulation and Prediction for the Poisson Spatial model
b50, p50 and b64

Simulated Data sets which Illustrate the Usage of the Package geoRglm
likfit.glsm

Monte Carlo Maximum Likelihood Estimation in a Generalised Linear Spatial Model
rongelap

Radionuclide Concentrations on Rongelap Island
lines.covariomodel

Line with a Covariogram Model
prior.glm.control

Defines prior options
prepare.likfit.glsm

Prepare for Monte Carlo MLE