Implements a class of spatio-temporal generalised linear mixed models for areal unit data, with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation. The response variable can be binomial, Gaussian or Poisson, but for some models only the binomial and Poisson data likelihoods are available. The spatio-temporal autocorrelation is modelled by random effects, which are assigned conditional autoregressive (CAR) style prior distributions. A number of different random effects structures are available, including Bernardinelli et al. (1995)
|Author||Duncan Lee, Alastair Rushworth and Gary Napier|
|Date of publication||2017-08-14 12:20:54 UTC|
|Maintainer||Duncan Lee <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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