Posterior outcome for "each subject" by Proc MCMC

[csfcgua1]

Hello, 

say I have a data set comprised of blood pressure measurements from N subjects. I would like to assign a status (1, 2, or 3) to each subject based on his/her blood pressure level, and the probability of being 1, 2, or 3 is a dirichlet distribution.

Data BP;
input ID BP;
datalines;
1 90
2 120
3 80
4 75
5 ...
;
run;

I modified the SAS official Example 75.1-Simulating Samples From a Known Density to perform the analysis:

proc mcmc data=BP outpost=simout seed=1234 nmc=30000 monitor=(z p);

     array ref_p[3] (0.3 0.4 0.3);

     array ref_mu[3] (70 100 130);

     parm z p mu;

     prior z ~ table(p);

     hyperprior p ~ dirich(ref_p);

     prior mu ~ normal(ref_mu[z], prec = 0.05);

     prior tau ~ gamma(0.1, iscale=0.1);

     model BP ~ normal(mu, prec = tau);
run;

The desired outcome would be like this:

ID p1     p2    p3    z
1  0.2    0.3   0.5   3
2  0.4    0.5   0.1   2
3  0.6    0.3   0.1   1
4 ...
...

but I only obtained an overall summary of z (mean of 2 since the second ref_p is the highest) for the whole group instead of for each subject.

Does anyone know how to modify the code so that I can assign which variables should be estimated for the whole group and which are by subject?

Thanks.

[csfcgua1]

Found the solution.

Just use the random statement for z, then everything works out.

random z ~ table(p) subject = id;