I'm using JAGS/rjags(3.3.0) for a Bayesian finite mixture and in so doing, trying to generate a multinomial with dirichlet priors. I receive the following error:

Error in jags.model(textConnection(coclust.jags), data = my.data, n.chains = 3, :

Error in node rtemp[6,225,1:2]

Unable to find appropriate sampler

(though the error occurs at various i,j positions, e.g. not always 6,225)

I've seen some examples where dmulti was replaced with a dsum of dpois variables but have not had success in implementing that solution. Any advice would be appreciated.

coclust.jags <-

"model{

for(i in 1:N){ # likelihood

for(j in 1:D){

x[i,j] ~ dbern(theta[rclass[i,j], cclass[i,j]])

rclass[i,j] <- inprod(rtemp[i,j,1:K], Kexpand[])

rtemp[i,j,1:K] ~ dmulti(pi[i,1:K],1)

cclass[i,j] <- inprod(ctemp[i,j,1:L], Lexpand[])

ctemp[i,j,1:L] ~ dmulti(pj[j,1:L],1)

}

}

for(k in 1:K){ # prior on theta for(l in 1:L){ theta[k,l] ~ dbeta(1, 1) } } for(i in 1:N) { # prior on rows pi[i,1:K] ~ ddirich(alpha1[1:K]+.001) # class prob pi } for(j in 1:D) { # prior on columns pj[j,1:L] ~ ddirich(alpha2[1:L]+.001) }

}"