Each table created by PROC FMM has a name associated with it, and you must use this name to reference the table when you use ODS statements. These names are listed in Table 39.9.
Table 39.9: ODS Tables Produced by PROC FMM
Table Name |
Description |
Required Statement / Option |
---|---|---|
AutoCorr |
Autocorrelation among posterior estimates |
|
BayesInfo |
Basic information about Bayesian estimation |
|
ClassLevels |
Level information from the CLASS statement |
|
CompDescription |
Component description in models with varying number of components |
|
CompEvaluation |
Comparison of mixture models with varying number of components |
|
CompInfo |
Component information |
COMPONENTINFO option in PROC FMM statement |
ConvergenceStatus |
Status of optimization at conclusion of optimization |
Default output |
Constraints |
Linear equality and inequality constraints |
RESTRICT statement or EQUATE= EFFECTS option in MODEL statement |
Corr |
Asymptotic correlation matrix of parameter estimates (ML) or empirical correlation matrix of the Bayesian posterior estimates |
|
Cov |
Asymptotic covariance matrix of parameter estimates (ML) or empirical covariance matrix of the Bayesian posterior estimates |
|
CovI |
Inverse of the covariance matrix of the parameter estimates |
|
ESS |
Effective sample sizes |
|
FitStatistics |
Fit statistics |
Default output |
Geweke |
Geweke diagnostics (Geweke, 1992) for Markov chains |
DIAG=GEWEKE option in BAYES statement |
Heidelberger |
Heidelberger and Welch diagnostics (Heidelberger and Welch, 1981, 1983) for Markov chains |
DIAG=HEIDELBERGER option in BAYES statement |
Hessian |
Hessian matrix from the maximum likelihood optimization, evaluated at the converged estimates |
|
IterHistory |
Optimizer iteration history |
Default output for maximum likelihood estimation; included in Bayesian estimation when BAYES statement includes the INITIAL= MLE option and PROC FMM statement includes the FITDETAILS option |
MCSE |
Monte Carlo standard errors |
DIAG=MCERROR in BAYES statement |
MixingProbs |
Solutions for the parameter estimates associated with effects in PROBMODEL statements |
Default output for ML estimation if number of components is greater than 1 |
ModelInfo |
Model information |
Default output |
NObs |
Number of observations read and used, number of trials and events |
Default output |
OptInfo |
Optimization information |
Default output for ML estimation |
ParameterEstimates |
Solutions for the parameter estimates associated with effects in MODEL statements |
Default output for ML estimation |
ParameterMap |
Mapping of parameter names to OUTPOST= data set |
|
PriorInfo |
Prior distributions and initial value of Markov chain |
|
PostSummaries |
Summary statistics for posterior estimates |
|
PostIntervals |
Equal-tail and highest posterior density intervals for posterior estimates |
|
Raftery |
Raftery and Lewis diagnostics (Raftery and Lewis, 1992, 1995) for Markov chains |
DIAG=RAFTERY option in BAYES statement |
ResponseProfile |
Response categories and category modeled |
Default output in models with binary response |