model { for( i in 1 : N ) { y[i] ~ dnorm(mu[i], tau) mu[i] <- lambda[T[i]] T[i] ~ dcat(P[]) } P[1:2] ~ ddirch(alpha[]) theta ~ dnorm(0.0, 1.0E-6)I(0.0, ) lambda[2] <- lambda[1] + theta lambda[1] ~ dnorm(0.0, 1.0E-6) tau ~ dgamma(0.01, 0.01) sigma <- 1 / sqrt(tau) } list(y = c(529.0, 530.0, 532.0, 533.1, 533.4, 533.6, 533.7, 534.1, 534.8, 535.3, 535.4, 535.9, 536.1, 536.3, 536.4, 536.6, 537.0, 537.4, 537.5, 538.3, 538.5, 538.6, 539.4, 539.6, 540.4, 540.8, 542.0, 542.8, 543.0, 543.5, 543.8, 543.9, 545.3, 546.2, 548.8, 548.7, 548.9, 549.0, 549.4, 549.9, 550.6, 551.2, 551.4, 551.5, 551.6, 552.8, 552.9,553.2), N = 48, alpha = c(1, 1), T = c(1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2)) list(lambda = c(535, NA), theta = 5, tau = 0.1)