I find the Winbugs code about GMCAR(α1, α2, η0, η1, τ 1, τ 2) model. (Xi Jin (2005) et.al)
but I want to fix this code to GMCAR(α, α, η0, 0, τ 1, τ 2) model.
Can someone help me?

I tried a lot to modify the code, but it doesn’t work. I would like you to modify the code.

`model <- {

  for (i in 1:N) {
    Y1[i] ~ dnorm(mu1[i], Tau)
    Y2[i] ~ dnorm(mu2[i], Tau)
    mu1[i] <- phi1[i]
    mu2[i] <- phi2[i]
  }

  for (i in 1:N) {
    m[i] <- 1 / num[i]  # scaling factor for variance in each county
  }

  for (i in 1:N) {
    mu_phi2[i] <- beta02

  for (j in 1:N) {
   count[i, j] <- W[i, j] * (phi2[j] - beta02)  # mean for phi_2
  }

    mu_phi1[i] <- beta01 + eta[1] * (phi2[i] - beta02) + eta[2] * sum(count[i, ])  
    # conditional mean for phi_1 | phi_2
  }

  #prior
  beta01 ~ dnorm(0, 1.0E-6)
  beta02 ~ dnorm(0, 1.0E-6)

  eta[1] ~ dnorm(0, 0.01)
  eta[2] ~ dnorm(0, 0.01)

  tau2 ~ dgamma(1, 0.1)
  tau1 ~ dgamma(1, 0.1)

  alpha ~ dunif(-0.999, 0.999)  # avoid improper CAR to maintain identifiability

  Tau
  sigma2 <- 1 / Tau
  sigmasq[1] <- 1 / tau[1]
  sigmasq[2] <- 1 / tau[2]

  phi2[1:N] ~ car.proper(mu_phi2[1:N], C[], adj[], num[], m[], tau[2], alpha)
  phi1[1:N] ~ car.proper(mu_phi1[1:N], C[], adj[], num[], m[], tau[1], alpha)

  ## set up the weight matrix C   
  cumsum[1] <- 0
  for (i in 2:(N + 1)) {
    cumsum[i] <- sum(num[1:(i - 1)])
  }

  for (kk in 1:sumNumNeigh) {
    for (i in 1:N) {
      pick[kk, i] <- step(kk - cumsum[i] - epsilon) * step(cumsum[i + 1] - kk)  # pick[kk, i] = 1 if     cumsum[i] < kk <= cumsum[i+1]; otherwise, pick[kk, i] = 0
    }
    C[kk] <- 1 / inprod(num[], pick[kk, ])  # weight for each pair of neighbours
  }

  epsilon <- 0.0001
}

`