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I hope everyone’s summer is going well. We were lucky enough to escape to the North Carolina mountains for a few weeks this month and avoided the worst of the heat. While the days in the NC mountains can still be quite warm, the nights are cool enough to really enjoy being outside.

In a previous newsletter, I mentioned the What’s New section of the SAS® Viya® programming documentation and using the Margins macro in working with marginal effects in generalized linear models. I am thrilled to see that we have added the MARGINS statement to PROC GLIMMIX in the SAS Viya 2021.1.3 release, available this month. You can read more about this statement in the 2021.1.3 SAS/STAT® User’s Guide. We look forward to seeing the MARGINS statement in other procedures in future releases of SAS Viya.

Our statistics team in SAS Technical Support has been together for quite some time. I would like to highlight a member of the team every few months so that you can get to know us a bit better. Among the 11 members of the team, we have over 260 years of experience supporting SAS software.

Paul Savarese joined SAS Technical Support in 1997. Paul has a PhD in statistics from Virginia Tech. His main area of specialty is survival models, but he also supports SAS procedures in quantile regression models. If you have sent questions to Tech Support about a procedure like PHREG or LIFETEST, you have most certainly benefitted from Paul’s thorough knowledge of this area of statistics. Paul enjoys the outdoors and lives in Madrid, Spain, with his wife, Maria, and their son, Pablo.

Our statistical procedures R&D team will host a virtual booth at this year’s American Statistical Association’s Joint Statistical Meetings. The conference begins August 8. If you are attending JSM this year, please stop by the online expo center and say hi!

Phil Gibbs

Manager, Advanced Analytics Technical Support


Technical Highlights


The DO Loop

Distinguished Research Statistician Developer Rick Wicklin explains the STDCOEF option in PROC GLIMMIX and how it differs from the STDB option in PROC REG, and he also discusses an outlier-detection method in time series analysis called the Hampel identifier. Learn about the Iman-Conover transformation and how to use it. Finally, Rick offers an introduction to simulating correlated data by using copulas.


The New solveBlackbox Action in SAS® Optimization

Ed Hughes, Steve Gardner, Josh Griffin, and Oleg Golovidov review the capabilities of the new solveBlackbox action in SAS Optimization and explore several examples of its use in a variety of settings. The solveBlackbox action is a valuable addition to SAS Optimization. It relies on the same derivative-free heuristic optimization algorithm that supports the black-box solver in SAS Optimization and hyperparameter tuning in SAS® Visual Data Mining and Machine Learning. Consequently, the solveBlackbox action can address a broad range of optimization problems that cannot be solved using traditional optimization solution algorithms.


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The SAS Data Science Blog

Yongqiao Xiao discusses how to streamline the scoring process of multiple analytic stores, while Hardi Desai talks about how she and her team were able to successfully develop and deploy a physical distance monitoring solution using computer vision for a SAS customer. Javier Schloemann how he and his team used SAS Viya to solve the problem of intelligently searching for new images in a large database of old images. Ricky Tharrington follows up his first post, an introduction to parallel processing, with this post that discusses parallel processing with CASL, the scripting language of the CAS server. And finally, Fijoy Vadakkumpadan gives you a behind-the-scenes look at the loadImages action in SAS Viya.


Semi-automatic Feature Engineering from Transactional Data

James Cox discusses a toolbox that he and his colleagues have been developing for transactional data and shows how to apply it to some real-world sample data. Note that this toolbox is extensible and modular, with an easy API that you can use to create more tools. Each tool consists of a SAS® Studio task and two SAS macros: one for training and another for scoring. The tools communicate with each other, both at training time and at scoring time, via SAS macro variables.


Tech Support Points Out

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Precision-Recall Curve for Imbalanced, Rare Event Data

The receiver operating characteristic (ROC) curve and the area beneath it (AUC-ROC) are perhaps the most commonly used graphic and statistic for assessing the performance of binary-response models or classifiers. However, as described by Saito and Rehmsmeier (2015) and others, the ROC curve and AUC-ROC can be misleading when the proportions of events and nonevents become very imbalanced. An example would be when there are very few observed events. They note that the statistics behind the ROC curve, sensitivity (also known as recall) and specificity, are invariant to the degree of imbalance. When interest focuses on the ability of the model to predict a high proportion of true events among the predicted events, known as the precision or positive predictive value (PPV), a plot involving that statistic can be more informative. The fact that the precision, unlike specificity, is sensitive to the degree of imbalance allows a plot of precision to more accurately reflect the measure of interest regardless of the degree of imbalance. This is the advantage of the precision-recall (PR) curve and the area under it (AUC-PR). The PRcurve macro plots precision against recall and computes the AUC-PR by using an appropriate interpolation method. Although linear interpolation can be used between points in ROC space, that is not the case in PR space. The macro can also find optimal points on the PR curve that have maximum values of the F score and Matthews correlation coefficient (MCC).


Talks and Tutorials

Ask the Expert

Ask the Expert: How Do I Authenticate to SAS Viya?

Tuesday, August 3 | 11:00 AM ET

To access SAS data, services, and APIs from outside SAS, you must first log in. This requires registering clients and creating access tokens to allow authentication to and authorization of SAS. Join this webinar to learn the various techniques to connect to SAS Viya. You will learn:

  • the basics of OAuth, the industry-standard protocol used to get access to protected data from an application
  • how SAS Viya uses these standards, with a demonstration of how developers and administrators can use simple commands such as curl to authenticate and access SAS Viya APIs
  • how to connect to SAS from various open source languages and technologies, such as Postman and Jupyter Notebook

Register Now


Ask the Expert

Ask the Expert: How Do I Use a Hash Object in Place of the LAG Function?

Thursday, August 19 | 11:00 AM ET

Join this webinar to learn how the LAG function works, to get an introduction to the hash object, and to understand why it can be helpful with autoregressive time series forecasting. The webinar will provide:

  • an in-depth discussion of the LAG function and a visual demonstration of how it works
  • an introduction to the hash object
  • a discussion of how to use a hash object to perform a LAG function when you need to do a calculation on the value

Register Now


Ask the Expert

Ask the Expert: How Do I Use SASPy to Interface with SAS from My Python Code?

Tuesday, August 24 | 11:00 AM ET

Join this webinar for an introduction to SASPy, our open source Python interface to SAS. We’ll explore use cases, resources, and capabilities. The webinar will provide:

  • a discussion of how to integrate your existing software systems with the latest open source language to write mixed workflows
  • a discussion of how SASPy can open SAS to Python programmers so they can use the best of both worlds together
  • a complete overview of SASPy, including documentation, support resources, use cases, and capabilities

Register Now



JSM 2021

August 8−12, 2021

SAS is a Gold Sponsor and will have a virtual EXPO booth.


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