Additional statistical capabilities in the containerized deployment of SAS Analytics Pro


In a September 10 post on the SAS Users blog, we announced that SAS Analytics Pro is now available for on-site or containerized cloud-native deployment. For our thousands of SAS Analytics Pro customers, this provides an entry point into SAS Viya.

SAS Analytics Pro consists of three core elements of the SAS system: Base SAS®, SAS/GRAPH® and SAS/STAT®. The containerized deployment option adds the full selection of SAS/ACCESS engines making it even easier to work with data from virtually any source.

Even better, the containerized deployment option now adds new statistical capabilities that are not available in SAS/STAT on SAS9. Thanks to SAS Viya’s continuous delivery approach, we are able to provide this additional functionality so soon after the initial release.

Below are highlights of these additional capabilities (you can find more details by following the links):

Causal Inference Procedures

Bayesian Analysis Procedures

  • Model multinomial data with cumulative probit, cumulative logit, generalized link, or other link functions in PROC BGLIMM.
  • Specify fixed scale values in a generalized linear mixed-effects model, and use an improved CMPTMODEL statement in PROC MCMC and PROC NLMIXED to fit compartment models.

Survey Procedures

Additional Capabilities:

For those SAS customers already on SAS Viya, or those considering the move, SAS Analytics Pro provides one more example of the new powers you will enjoy!


About Author

Mike Gilliland

Product Marketing Manager

Michael Gilliland is a longtime business forecasting practitioner and formerly a Product Marketing Manager for SAS Forecasting. He is on the Board of Directors of the International Institute of Forecasters, and is Associate Editor of their practitioner journal Foresight: The International Journal of Applied Forecasting. Mike is author of The Business Forecasting Deal (Wiley, 2010) and former editor of the free e-book Forecasting with SAS: Special Collection (SAS Press, 2020). He is principal editor of Business Forecasting: Practical Problems and Solutions (Wiley, 2015) and Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Wiley, 2021). In 2017 Mike received the Institute of Business Forecasting's Lifetime Achievement Award. In 2021 his paper "FVA: A Reality Check on Forecasting Practices" was inducted into the Foresight Hall of Fame. Mike initiated The Business Forecasting Deal blog in 2009 to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

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