netcmc

Implements a class of univariate and multivariate spatio-network generalised linear mixed models for areal unit and network 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 that are assigned a conditional autoregressive (CAR) prior distribution following the Leroux model (Leroux et al. (2000) doi:10.1007/978-1-4612-1284-3_4). Network structures are modelled by a set of random effects that reflect a multiple membership structure (Browne et al. (2001) doi:10.1177/1471082X0100100202).