R/ST.CARsepspatial.R

In CARBayesST: Spatio-Temporal Generalised Linear Mixed Models for Areal Unit Data

ST.CARsepspatial <- function(formula, family, data=NULL, trials=NULL, W, burnin, n.sample, thin=1, n.chains=1, n.cores=1, prior.mean.beta=NULL, prior.var.beta=NULL, prior.tau2=NULL, rho.S=NULL, rho.T=NULL, MALA=TRUE, verbose=TRUE)
{
  ## This is a wrapper function for the following two functions.
  ## binomial.CARepspatial
  ## poisson.CARepspatial
  if(is.null(family)) stop("the family argument is missing", call.=FALSE)

  #### Run the appropriate model according to the family arugment
  if(family=="binomial")
  {
    if(is.null(trials)) stop("a binomial model was specified but the trials arugment was not specified", call.=FALSE)
    model <- binomial.CARsepspatial(formula=formula, data=data, trials=trials, W=W, burnin=burnin, n.sample=n.sample, thin=thin, n.chains=n.chains, n.cores=n.cores, prior.mean.beta=prior.mean.beta, prior.var.beta=prior.var.beta, prior.tau2=prior.tau2, rho.S=rho.S, rho.T=rho.T,  MALA=MALA, verbose=verbose)
  }else if(family=="poisson")
  {
    if(!is.null(trials)) stop("you do not need a trials arugment as a binomial model was not specified", call.=FALSE)
    model <- poisson.CARsepspatial(formula=formula, data=data, W=W, burnin=burnin, n.sample=n.sample, thin=thin, n.chains=n.chains, n.cores=n.cores, prior.mean.beta=prior.mean.beta, prior.var.beta=prior.var.beta, prior.tau2=prior.tau2, rho.S=rho.S, rho.T=rho.T,  MALA=MALA, verbose=verbose)          
  }else
  {
    stop("the family arugment is not one of `binomial' or `poisson'.", call.=FALSE)
  }
  return(model)     
}