model
{
	Tau.noninformative <- 1.0E-4
	for (i in 1:N.sector) {
		# observation
		Disturbance[i] ~ dbin(p[i], N.dist)
		logit(p[i]) <- (
			(x[i] - N.size * 0.5) * 10 / N.size
			+ b * Distance[i]
		)
		# latent variable
		x[i] ~ dbin(q[i], N.size)
		logit(q[i]) <- (
			a[1, Tr[i]]
			+ a[2, Tr[i]] * (x[LeftRight[i, 1]] + x[LeftRight[i, 2]]) / N.size
		)
	}
	# parameters
	for (j in 1:N.a) {
		for (k in 1:N.transect) {
			a[j, k] ~ dnorm(0, Tau.noninformative)
		}
	}
	b ~ dnorm(0, Tau.noninformative)
}