# data section for JAGS
data{for(i in 1:n){zeros[i] <- 0}}

model{

	# Likelihood

	for(i in 1:n){

	mu[i] <- beta[1]*intercept.sim[i] +
		beta[2]*x1[i] +
		beta[3]*x2[i] +
		(1 - 2*tau)*w[i]/(tau*(1 - tau))

	prec[i] <- delta*tau*(1 - tau)/(2*w[i])

	log.like[i] <- 0.5*log(prec[i]/(2*3.14159)) - 0.5*pow(q.transformed[i] - mu[i], 2)*prec[i]

	#	zeros trick

	zeros[i] ~ dpois(lambda[i])

	lambda[i] <- -log.like[i] + 10000

	}

	# prior distributions

	beta[1] ~ dunif(0, 1)
	beta[2] ~ dunif(0, 3)
	beta[3] ~ dunif(-10, 10)

	delta ~ dgamma(0.001, 0.001)


	for(i in 1:n){w[i] ~ dexp(delta)}


}