Camel: Multivariate normal with structured missing data

Tanner and Wong present a data set with missing values modeled as a bivariate normal. No closed form for the deviance of the model can be found and so no deviance node is created by the BUGS compiler. For the same reason the DIC menu is greyed-out
   model
   {
      for (i in 1 : N){
         Y[i, 1 : 2] ~ dmnorm(mu[], tau[ , ])
      }
      mu[1] <- 0
      mu[2] <- 0
      tau[1 : 2,1 : 2] ~ dwish(R[ , ], 2)
      R[1, 1] <- 0.001
      R[1, 2] <- 0
      R[2, 1] <- 0;
      R[2, 2] <- 0.001
      Sigma2[1 : 2,1 : 2] <- inverse(tau[ , ])
      rho <- Sigma2[1, 2] / sqrt(Sigma2[1, 1] * Sigma2[2, 2])
   }
Data
list(N= 12,
         Y = structure(
            .Data = c(1,1,
            1,-1,
            -1,1,
            -1, -1,
            2, NA,
            2, NA,
            -2, NA,
            -2, NA,
            NA, 2,
            NA, 2,
            NA, -2,
            NA, -2),
            .Dim = c(12, 2)))
Inits for chain 1
list(tau = structure(.Data = c(0.1,0,0,0.1), .Dim = c(2,2)),
      Y = structure(
            .Data = c(NA,NA,
            NA,NA,
            NA,NA,
            NA, NA,
            NA, 1,
            NA, 1,
            NA, 1,
            NA, 1,
            1, NA,
            1, NA,
            1, NA,
            1, NA),
            .Dim = c(12, 2)))
   
Inits for chain 2
list(tau = structure(.Data = c(0.5,0,0,0.5), .Dim = c(2,2)),
      Y = structure(
            .Data = c(NA,NA,
            NA,NA,
            NA,NA,
            NA, NA,
            NA, 2,
            NA, 2,
            NA, 2,
            NA, 2,
            3, NA,
            3, NA,
            3, NA,
            3, NA),
            .Dim = c(12, 2)))

Results

[camel1]

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