R/B2ZM_MCMC.R

In B2Z: Bayesian Two-Zone Model

B2ZM_MCMC <- function(data, priorBeta, priorQ, priorG, v, S, 
                      tauN.sh, tauN.sc, tauF.sh, tauF.sc,  
                      VN, VF, indep.model = FALSE, cred = 95,  
                      NUpd = 10000, burnin = 1000, lag = 1, 
                      initial = NULL, Sigma.Cand = NULL, 
                      m = 6000, figures = list(save = FALSE, 
                      type =c("ps", "eps","pdf", "png", "jpg"))) {

   if(!indep.model){
      tauN.sh = tauN.sc = tauF.sh = tauF.sc = 0
   }
   else{
      S <- matrix(0,2,2)
      v <- 0
   }

   ans <- B2ZM(data = data, priorBeta = priorBeta, priorQ = priorQ, 
               priorG = priorG, v = v, S = S, tauN.sh = tauN.sh, 
               tauN.sc = tauN.sc, tauF.sh = tauF.sh, tauF.sc = tauF.sc, 
               VN = VN, VF = VF, indep.model = indep.model, 
               cred = 95,  sampler = "MCMC",  mcmc.control = list(NUpd = NUpd, 
               burnin = burnin, lag = lag, initial = initial, Sigma.Cand = Sigma.Cand, 
               m = m), figures = figures)

   return(ans)
   }