model {
   tau ~ dunif(1e-8,1e8)
   logsigma ~ dunif(-1e8,1e8)
   mu ~ dunif(-1e8,1e8)
   for (j in 1:J) {
       theta[j] ~ dnorm(mu,tau^(-2))
       for (i in 1:n[j]) {
	   y[sum(n[1:j]) - (i-1)] ~ dnorm(theta[j],exp(-2*logsigma))
       }
   }
}