RJAGS Multinomial-Dirichlet – Observed node inconsistent with unobserved parents at initialization I am trying to model a simple 2x2 contingency table with a multinomial-Dirichlet model. 
A snippet of my data z[i,1:4] look like this:
        NFF NFS NSF NSS
  [1,]  12  52  52  61
  [2,]   5   2   2  28
  [3,]   4   8   8 159
  [4,]  27  34  34  60
  [5,]  16  27  27  61
        …
  [207,]

Here is my model file:
    model
       {
        for (j in 1:K)
          {
           alpha[j] ~ dbeta(a[j],b[j])
            a[j]~ dgamma(0.0001, 0.0001)
            b[j]~ dgamma(0.0001, 0.0001)
           }

            pi ~ ddirch(alpha[1:K])
            total ~ dpois(rate)
            rate ~ dgamma(0.0001, 0.0001)

             for (i in 1:N)
                 { z[i, 1:K] ~ dmulti(pi, total)}
         }

My RJAGS calls look like this:
    z<-as.matrix(infile)
    K<-ncol(z)
    N<-nrow(z)
    data <- list("z" = z, "N" = N,"K"= K)
    jags.m <- jags.model(file="multinomialmodeloriginal4.jag", data = data,n.chains = 3, n.adapt = 1000)

Unfortunately, I run into the following error messages:
   Compiling model graph
   Resolving undeclared variables
   Allocating nodes
   Graph Size: 226

   Initializing model
   Deleting model
   Error in jags.model(file = "multinomialmodeloriginal5.jag", data = data,  : 
   Error in node z[1,1:4]
   Observed node inconsistent with unobserved parents at initialization

Any suggestions on how to address the initialization error is appreciated. I am a newbie!!
 A: 
Any suggestions on how to address the initialization error is appreciated.

A good start would be to actually initialize the parameters :) The problem is that if not initialized correctly, total might be a small number, say 5, which is less than z[1,1:4], which means that a z[1,1:4] of 12 would be logically impossible, hence the error Observed node inconsistent with unobserved parents at initialization.
Just initialize total to something safe like max(z) + 1:
    jags.m <- jags.model(file="multinomialmodeloriginal4.jag", data = data,n.chains = 3, n.adapt = 1000, inits=list(total = max(z) + 1))

Edit:
Ok, in general you get the error Observed node inconsistent with unobserved parents at initialization for the reasons I specified above. But when I look more closely at your code, I'm not sure that any initialization will work. The problem is that for each row of z you know the length, it can't be anything else than the sum of that row. Therefore it it very strange that you have it as a parameter, as it should just be a variable. try creating a vector length[i] with this property and give it as a variable to JAGS.
If you want to keep total in your model there is nothing stopping you from doing that. If you have created the vector length that conains the sums of each row in z then you can add something like the following statement in you for loop
...
  length[i] ~ dpois(total)
}
total ~dunif(0, 999) # Or whatever prior you think is suitable.

