model{
   # Decision data
   for(k in 1:nsubj){
      for(i in 1:nstim){
         y[i,k]~dbin(r[i,k],t)
         pred[i,k]~dbin(r[i,k],t)
      }
   }
   # Similarity computation
   for(k in 1:nsubj){
      for(i in 1:nstim){
         for(j in 1:nstim){
            s[i,j,k]<-exp(-c[k]*(w[k]*d1[i,j]+(1-w[k])*d2[i,j]))
         }
      }
   }
   # Check if exemplar belongs to Category 1
   for(j in 1:nstim){
         index1[j]<-1*(a[j]==1)+0*(a[j]==2)
         index2[j]<-1-index1[j]
   }
   # Decision probability
   for(k in 1:nsubj){
      for(i in 1:nstim){
         temp1[i,k]<-inprod(s[i,,k],index1)
         temp2[i,k]<-inprod(s[i,,k],index2)
         r[i,k]<-temp1[i,k]/(temp1[i,k]+temp2[i,k])
      }
   }
   # Priors
   for(k in 1:nsubj){
      c[k]~dunif(0,5)
      w[k]~dbeta(1,1)
   }
}