model{
  alpha ~ dnorm(0,0.001)
  beta ~ dnorm(0,0.001)T(0,) #Truncated distribution
  for(i in 1:k){
    logit(theta[i]) <- alpha+beta*x[i]
    y[i] ~ dbinom(theta[i],n[i]) 
  } 
  LD50 <- -alpha/beta
  for(i in 1:K){
    logit(theta.pred[i]) <- alpha+beta*xpred[i]
  }
}