Implements a class of univariate and multivariate spatial 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, multinomial, Poisson or zeroinflated Poisson (ZIP), and spatial autocorrelation is modelled by a set of random effects that are assigned a conditional autoregressive (CAR) prior distribution. A number of different models are available for univariate spatial data, including models with no random effects as well as random effects modelled by different types of CAR prior, including the BYM model (Besag et al. (1991) <doi:10.1007/BF00116466>), the Leroux model (Leroux et al. (2000) <doi:10.1007/9781461212843_4>) and the localised model (Lee et al. (2015) <doi:10.1002/env.2348>). Additionally, a multivariate CAR (MCAR) model for multivariate spatial data is available, as is a twolevel hierarchical model for modelling data relating to individuals within areas. Full details are given in the vignette accompanying this package. The initial creation of this package was supported by the Economic and Social Research Council (ESRC) grant RES000224256, and ongoing development has been supported by the Engineering and Physical Science Research Council (EPSRC) grant EP/J017442/1, ESRC grant ES/K006460/1, Innovate UK / Natural Environment Research Council (NERC) grant NE/N007352/1 and the TB Alliance.
Package details 


Author  Duncan Lee 
Maintainer  Duncan Lee <Duncan.Lee@glasgow.ac.uk> 
License  GPL (>= 2) 
Version  5.2 
URL  http://github.com/duncanplee/CARBayes 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

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