model
{	
	for(i in 1 : M) {
		for(j in 1 : N) {                          
			t[i, j] ~ dweib(r, mu[i])I(t.cen[i, j],)
		}
		mu[i] <- exp(beta[i])
		beta[i] ~ dnorm(0.0, 0.001)
		median[i] <- pow(log(2) * exp(-beta[i]), 1/r)  
	}	
	r ~ dexp(0.001)
	veh.control <- beta[2] - beta[1]     
	test.sub <- beta[3] - beta[1]
	pos.control <- beta[4] - beta[1]
}