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 or Poisson. Spatial autocorrelation is modelled by a set of random effects, which are assigned a conditional autoregressive (CAR) prior distribution. A number of different CAR priors are available for the random effects, including a multivariate CAR (MCAR) model for multivariate spatial data. 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 RES-000-22-4256, and on-going development was supported by the Engineering and Physical Science Research Council (EPSRC) grant EP/J017442/1.
|Date of publication||2017-02-01 16:12:02|
|Maintainer||Duncan Lee <Duncan.Lee@glasgow.ac.uk>|
|License||GPL (>= 2)|
CARBayes-package: Spatial Generalised Linear Mixed Models for Areal Unit Data
coef.CARBayes: Extract the regression coefficients from a model.
combine.data.shapefile: Combines a data frame with a shapefile to create a...
fitted.CARBayes: Extract the fitted values from a model.
highlight.borders: Creates a SpatialPoints object identifying a subset of...
logLik.CARBayes: Extract the estimated loglikelihood from a fitted model.
model.matrix.CARBayes: Extract the Model (design) matrix from a model.
MVS.CARleroux: Fit a multivariate spatial generalised linear mixed model to...
print.CARBayes: Print a summary of a fitted CARBayes model to the screen.
residuals.CARBayes: Extract the residuals from a model.
S.CARbym: Fit a spatial generalised linear mixed model to data, where...
S.CARdissimilarity: Fit a spatial generalised linear mixed model to data, where...
S.CARleroux: Fit a spatial generalised linear mixed model to data, where...
S.CARlocalised: Fit a spatial generalised linear mixed model to data, where a...
summarise.lincomb: Compute the posterior distribution for a linear combination...
summarise.samples: Summarise a matrix of Markov chain Monte Carlo samples.