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CARBayesST (version 1.0)

Poisson Log-linear Models with Spatio-temporal Random Effects

Description

Implements a series of Poisson log-linear models with spatio-temporal random effects. The spatial and temporal autocorrelation in the random effects are induced using the class of Conditional AutoRegressive (CAR) priors, which are a special case of Gaussian Markov Random Fields (GMRF). All models are fitted in a Bayesian context using Markov chain Monte Carlo (McMC) simulation.

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Version

Install

install.packages('CARBayesST')

Monthly Downloads

437

Version

1.0

License

GPL (>= 2)

Maintainer

Duncan Lee

Last Published

August 11th, 2014

Functions in CARBayesST (1.0)

ST.clustonly

Fit the cluster only Poisson log-linear model proposed by Lee and Lawson (2014).
CARBayesST-package

Poisson Log-linear Models with Spatio-temporal Random Effects
ST.knorrheld.int

Fit the space-time Poisson log-linear model proposed by Knorr-Held (2000) with separable spatio-temporal main effects and an independent space-time interaction.
print.carbayesST

Print a summary of the fitted model to the screen.
results.summarise

Summarise a matrix of Markov chain Monte Carlo samples.
ST.knorrheld.main

Fit the separable space-time Poisson log-linear model proposed by Knorr-Held and Besag (1998).
ST.clustcar

Fit the cluster car Poisson log-linear model proposed by Lee and Lawson (2014).
ST.clustconv

Fit the cluster conv Poisson log-linear model proposed by Lee and Lawson (2014).