The MCMC Procedure |
The following statements can be used with PROC MCMC:
The PARMS statements declare parameters in the model and assign optional starting values for the Markov chain. The PRIOR/HYPERPRIOR statements specify the prior distributions of the parameters. The MODEL statements specify the log-likelihood functions for the response variables. These statements form the basis of every Bayesian model.
In addition, you can use the ARRAY statement to define constant or parameter arrays, the BEGINCNST/ENDCNST and similar statements to save unnecessary evaluation and reduce simulation time, the program statements to specify more complicated models that you wish to fit, and finally the UDS statements to define your own Gibbs samplers to sample any parameters in the model.
The following sections provide a description of each of these statements.
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