The MCMC Procedure

ODS Table Names

PROC MCMC assigns a name to each table it creates. You can use these names to refer to the table when you use the Output Delivery System (ODS) to select tables and create output data sets. These names are listed in Table 55.47. For more information about ODS, see Chapter 21: Statistical Graphics Using ODS.

Table 55.47: ODS Tables Produced in PROC MCMC

ODS Table Name	Description	Statement or Option
AutoCorr	Autocorrelation statistics for each parameter	Default
BurnInHistory	History of burn-in phase sampling	MCHISTORY=BRIEF \| DETAILED
ConvergenceStatus	Optimization convergence status	PROPCOV=`method`(ITPRINT)
Corr	Correlation matrix of the posterior samples	STATS=CORR
Cov	Covariance matrix of the posterior samples	STATS=COV
DIC	Deviance information criterion	DIC
ESS	Effective sample size for each parameter	Default
MCSE	Monte Carlo standard error for each parameter	Default
Geweke	Geweke diagnostics for each parameter	Default
Heidelberger	Heidelberger-Welch diagnostics for each parameter	DIAGNOSTICS=HEIDEL
InputOptions	Optimization input table	PROPCOV=`method`(ITPRINT)
IterHist	Optimization iteration history	PROPCOV=`method`(ITPRINT)
IterStop	Optimization results table	PROPCOV=`method`(ITPRINT)
MissDataInfo	Response variable, number of missing observations, missing observation indices, and sampling algorithm	Default with sampling of missing values
NObs	Number of observations	Default
OptiEstimates	Parameter values after either optimization	PROPCOV=`method`(ITPRINT)
OptiCov	Covariance used in proposal distribution after optimization	PROPCOV=`method`(ITPRINT)
Parameters	Summary of the PARMS, BLOCKING, PRIOR, sampling method, and initial value specification	Default
ParametersInit	Parameter values after the tuning phase	INIT=PINIT
PosteriorSample	Posterior samples for each parameter	(For ODS output data set only)
PostIntervals	Equal-tail and HPD intervals for each parameter	Default
PostSummaries	Basic posterior statistics for each parameter, including sample size, mean, standard deviation, and percentiles	Default
PredIntervals	Equal-tail and HPD intervals for each prediction	Default with any PREDDIST statement
PredSummaries	Basic posterior statistics for each prediction	Default with any PREDDIST statement
ProblemDescription	Optimization table	PROPCOV=`method`(ITPRINT)
REObsInfo	Random effect, subject values, number of observations in each unique subject value, and corresponding observation indices	REOBSINFO
REParameters	Random effect, sampling method, subject variable, number of subjects, unique values of the subject variable, and prior distribution of the random effect	Default with any RANDOM statement
Raftery	Raftery-Lewis diagnostics for each parameter	DIAGNOSTICS=RAFTERY
SamplingHistory	History of main phase sampling	MCHISTORY=BRIEF \| DETAILED
TuneCov	Proposal covariance matrix (for continuous parameters) after the tuning phase	INIT=PINIT
TuneP	Proposal probability vector (for discrete parameters) after the tuning phase	INIT=PINIT and DISCRETE=GEO
TuningHistory	History of proposal distribution tuning	MCHISTORY=BRIEF \| DETAILED