	model
	{
		for( i in 1 : N ) {
			Y[i] ~ dnorm(mu[i], tau)
			mu[i] <- alpha - beta * pow(gamma,x[i])			
		}
		alpha ~ dnorm(0.0, 1.0E-6)
		beta ~ dnorm(0.0, 1.0E-6)
		gamma ~ dunif(0.5, 1.0)
		tau ~ dgamma(0.001, 0.001)
		sigma <- 1 / sqrt(tau)
		U3 <- logit(gamma)	
	}
