The LIFEREG Procedure |
ODS Table Names |
PROC LIFEREG assigns a name to each table it creates. You can use these names to reference the table when using the Output Delivery System (ODS) to select tables and create output data sets. These names are listed separately in Table 48.4 for a maximum likelihood analysis and in Table 48.5 for a Bayesian analysis. For more information about ODS, see Chapter 20, Using the Output Delivery System.
ODS Table Name |
Description |
Statement |
Option |
---|---|---|---|
ClassLevels |
Classification variable levels |
CLASS |
default |
ConvergenceStatus |
Convergence status |
MODEL |
default |
CorrB |
Parameter estimate correlation matrix |
MODEL |
CORRB |
CovB |
Parameter estimate covariance matrix |
MODEL |
COVB |
IterEM |
Iteration history for Turnbull algorithm |
PROBPLOT |
ITPRINTEM |
FitStatistics |
Fit statistics |
MODEL |
default |
IterHistory |
Iteration history |
MODEL |
ITPRINT |
LagrangeStatistics |
Lagrange statistics |
MODEL |
NOINT | NOSCALE |
LastGrad |
Last evaluation of the gradient |
MODEL |
ITPRINT |
LastHess |
Last evaluation of the Hessian |
MODEL |
ITPRINT |
ModelInfo |
Model information |
MODEL |
default |
NObs |
Number of observations |
MODEL |
default |
ParameterEstimates |
Parameter estimates |
MODEL |
default |
ParmInfo |
Parameter indices |
MODEL |
default |
ProbabilityEstimates |
Nonparametric CDF estimates |
PROBPLOT |
PPOUT |
TConvergenceStatus |
Convergence status for Turnbull algorithm |
PROBPLOT |
default |
Turnbull |
Probability estimates from Turnbull algorithm |
PROBPLOT |
ITPRINTEM |
Type3Analysis |
Type 3 tests |
MODEL |
default |
Depends on data.
ODS Table Name |
Description |
Statement |
Option |
---|---|---|---|
AutoCorr |
Autocorrelations of the posterior samples |
BAYES |
default |
ClassLevels |
Classification variable levels |
CLASS |
default |
CoeffPrior |
Prior distribution of the regression coefficients |
BAYES |
default |
ConvergenceStatus |
Convergence status of maximum likelihood estimation |
MODEL |
default |
Corr |
Correlation matrix of the posterior samples |
BAYES |
SUMMARY=CORR |
ESS |
Effective sample size |
BAYES |
default |
FitStatistics |
Fit statistics |
BAYES |
default |
Gelman |
Gelman and Rubin convergence diagnostics |
BAYES |
DIAG=GELMAN |
Geweke |
Geweke convergence diagnostics |
BAYES |
default |
Heidelberger |
Heidelberger and Welch convergence diagnostics |
BAYES |
DIAG=HEIDELBERGER |
InitialValues |
Initial values of the Markov chains |
BAYES |
default |
ModelInfo |
Model information |
MODEL |
default |
NObs |
Number of observations |
MODEL |
default |
ParameterEstimates |
Maximum likelihood estimates of model parameters |
MODEL |
default |
ParmPrior |
Prior distribution for scale and shape |
BAYES |
default |
PostIntervals |
HPD and equal-tail intervals of the posterior samples |
BAYES |
default |
PosteriorSample |
Posterior samples (for output data set only) |
BAYES |
|
PostSummaries |
Summary statistics of the posterior samples |
BAYES |
default |
Raftery |
Raftery and Lewis convergence diagnostics |
BAYES |
DIAG=RAFTERY |
Depends on data.
Copyright © 2009 by SAS Institute Inc., Cary, NC, USA. All rights reserved.