| CARBayes-package | Spatial Generalised Linear Mixed Models for Areal Unit Data |
| CARBayes | 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 SpatialPolygonsDataFrame object. |
| fitted.CARBayes | Extract the fitted values from a model. |
| highlight.borders | Creates a SpatialPoints object identifying a subset of borders between neighbouring areas. |
| 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 data, where the random effects are modelled by a multivariate conditional autoregressive model. |
| 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 the random effects have a BYM conditional autoregressive prior. |
| S.CARdissimilarity | Fit a spatial generalised linear mixed model to data, where the random effects have a localised conditional autoregressive prior. |
| S.CARleroux | Fit a spatial generalised linear mixed model to data, where the random effects have a Leroux conditional autoregressive prior. |
| S.CARlocalised | Fit a spatial generalised linear mixed model to data, where a set of spatially smooth random effects are augmented with a piecewise constant intercept process. |
| S.CARmultilevel | Fit a spatial generalised linear mixed model to multi-level areal unit data, where the spatial random effects have a Leroux conditional autoregressive prior and there are also individual or small group level random effects. |
| S.glm | Fit a generalised linear model to data. |
| summarise.lincomb | Compute the posterior distribution for a linear combination of the covariates from the linear predictor. |
| summarise.samples | Summarise a matrix of Markov chain Monte Carlo samples. |