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]
}