Usage Note 23407: What Bayesian methods are available?
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Below is a summary of the available Bayesian methods and the procedures in which they appear:
| Product | Beginning Release | Procedure | Bayesian Methodology |
| SAS/STAT | SAS 6 | DISCRIM | Computes posterior probabilities of group membership and posterior probability error rate estimates. Specifies prior probabilities of group membership in the PRIORS statement. |
| GLM | The WALLER option provides multiple comparisons of means, minimizing Bayes risk under additive loss. | ||
| LOGISTIC | The CTABLE option estimates false positive and false negative rates as posterior probabilities using Bayes theorem. The PEVENT= option provides prior probabilities. | ||
| SAS 7 | MIXED | The PRIOR statement specifies prior distribution for variance components and estimates their marginal posterior density. | |
| SAS 8 | NLMIXED | The PREDICT statement and the OUT= option in the RANDOM statement provide empirical Bayes estimates of random effects. | |
| TPSPLINE | The OUTPUT statement can request Bayesian confidence intervals for smoothing spline estimates. | ||
| SAS 8.1 | GAM | The OUTPUT statement can request Bayesian confidence intervals for smoothing spline estimates. | |
| MI | Can perform an approximate Bayesian bootstrap imputation of missing values. Prior information for Bayesian estimation of means and covariances can be supplied by using the PRIOR= option in the MCMC statement. | ||
| SAS 9.2 | GENMOD LIFEREG PHREG |
The BAYES statement requests a Bayesian analysis of the regression model using Gibbs sampling. The model parameters are treated as random variables, prior distributions can be specified, and inferences about the parameters are based on the posterior distribution of the parameters given the data. | |
| MCMC | (Experimental) MCMC is a general purpose Markov chain Monte Carlo simulation procedure that fits Bayesian models given arbitrary prior distributions for the model parameters and a likelihood function for the data. MCMC obtains samples from the posterior distributions, produces summary and diagnostic statistics, and saves the posterior samples in an output data set. | ||
| SAS/QC | SAS 6 | ADX application | Can perform Bayesian selection of active effects in saturated and nearly saturated designs. Prior probabilities of active effects can be specified. |
| BAYESACT function | Computes posterior probabilities that observations in a sample are contaminated with a larger variance than other observations. Computes the posterior probability that the entire sample is uncontaminated. | ||
| OPTEX | Can search for a Bayesian optimal design. Specifies prior precision values in the PRIORS= option in the MODEL statement. | ||
| SAS/ETS | SAS 8 | VARMAX | Can fit the Bayesian Vector AutoRegressive model and the Bayesian Vector Error Correction model. Specifies prior information by using the PRIOR= option in the MODEL statement. |
| SAS/IML | SAS 6 | TSBAYSEA function | Performs Bayesian seasonal adjustment modeling. |
| SAS/Genetics | SAS 9.1 TS1M3 | HAPLOTYPE | Haplotype frequency estimation. |
| † Book-Based Macros | Multiple Comparisons and Multiple Tests Using the SAS System | %BayesIntervals | Computes Bayesian simultaneous confidence intervals. |
| %BayesTests | A SAS/IML macro that computes Bayesian posterior probabilities for a set of free-combination tests. |
† See the associated book for information about the use and output from these macros.
Operating System and Release Information
| Product Family | Product | System | SAS Release | |
| Reported | Fixed | |||
| SAS System | SAS/ETS | All | n/a | |
| SAS System | SAS/IML Workshop | All | n/a | |
| SAS System | SAS/QC | All | n/a | |
| SAS System | SAS/STAT | All | n/a | |
| Type: | Usage Note |
| Priority: | low |
| Topic: | Analytics ==> Survival Analysis SAS Reference ==> Procedures ==> TPSPLINE SAS Reference ==> Procedures ==> MI Analytics ==> Regression SAS Reference ==> Procedures ==> GAM Analytics ==> Nonparametric Analysis Analytics ==> Multivariate Analysis SAS Reference ==> Procedures ==> NLMIXED Analytics ==> Mixed Models SAS Reference ==> Procedures ==> GLM SAS Reference ==> Procedures ==> LOGISTIC SAS Reference ==> Procedures ==> DISCRIM Analytics ==> Missing Value Imputation Analytics ==> Longitudinal Analysis Analytics ==> Forecasting Analytics ==> Discriminant Analysis SAS Reference ==> Procedures ==> MIXED Analytics ==> Design of Experiments SAS Reference ==> Procedures ==> VARMAX Analytics ==> Categorical Data Analysis SAS Reference ==> Procedures ==> OPTEX Analytics ==> Analysis of Variance SAS Reference ==> Procedures ==> GENMOD SAS Reference ==> Procedures ==> LIFEREG SAS Reference ==> Procedures ==> MCMC SAS Reference ==> Procedures ==> PHREG Analytics ==> Time Series Analysis Analytics |
| Date Modified: | 2007-10-05 13:44:27 |
| Date Created: | 2003-09-19 10:01:23 |
