model{
   # Decision data
   for(i in 1:nstim){
      y[i]~dbin(r[i],t)
      pred[i]~dbin(r[i],t)
   }
   # Similarity computation
   for(i in 1:nstim){
      for(j in 1:nstim){
         s[i,j]<-exp(-c*(w*d1[i,j]+(1-w)*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(i in 1:nstim){
      temp1[i]<-inprod(s[i,],index1)
      temp2[i]<-inprod(s[i,],index2)
      r[i]<-temp1[i]/(temp1[i]+temp2[i])
   }
   # Priors
   c~dunif(0,5)
   w~dbeta(1,1)
}