Explore. Share. Code.

The starting point for your SAS® and Viya™ projects

Articles
Technical Articles

Discover technical articles from the community

Code SAS
SAS® Code

Snippets & Tutorials

FAQ
Q&A Base

FAQ & Help

Scenarios
Scenarios

Business Use Cases

CAS Actions
CAS Actions

Full Catalog & Examples

Data Step
Data Step

Preparation Scripts

Python
Python

SAS & Python Integration

Blog
Blog

News, tech watch and site updates

Join the community

Participate in the life of the site

Community by the numbers

0
Documented Actions
0
Code Examples
0
Articles Techniques
0
Scénarios Métiers
0
Solved Questions

Latest Articles

Stress Test & Benchmarking SAS Viya: Efficiently saturating your CAS CPU cores
23/12
SAS Viya Programming Guide
Mastering Resource Allocation in SAS Viya: An Expert's Guide to Launcher Contexts
21/12
Guide SAS VIYA
Optimizing the Data Step in SAS Viya: The Expert Guide
10/12
Guide SAS VIYA
View articles   Knowledge Hub

Top 3 Popular

1
accessPersonalCaslibs
accessControl
133
2
addCaslib
table
88
3
aggregate
aggregation
81

Discover

iml
iml

Submits SAS/IML programs in CAS....

crfTrain
conditionalRandomFields

The crfTrain action trains a Conditional Random Fields (CRF) model for sequence ...

listRegions
s3

The listRegions action lists all the S3 regions that are defined for the CAS ser...

Random FAQ

What parameter is used to control the display of metrics?

The 'on' parameter specifies whether a brief set of action metrics is displayed.

See answer
On: metrics
What is the 'table.computedVars.label' subparameter?

The 'table.computedVars.label' subparameter specifies the descriptive label for the variable.

See answer
On: groupBy
How can I specify which variables to analyze for missing patterns?

You can use the 'inputs' parameter to provide a list of variables to be included in the analysis. If this parameter is not specified, the action may use a default set of variables from the input table.

See answer
On: analyzeMissingPatterns
What is the difference between the 'IPW' and 'AIPW' methods?

The 'IPW' (Inverse Probability Weighting) method requires the observed outcome and predicted treatment probabilities. The 'AIPW' (Augmented Inverse Probability Weighting) method is a doubly robust method that also requires predicted counterfactual outcome values in addition to what IPW requires.

See answer
On: caEffect
How do I perform nonnegative factorization with the factmac action?

You can set the "nonNegative" parameter to TRUE. The default behavior is FALSE.

See answer
On: factmac
See full FAQ
Copyright © WeAreCAS 2014-2026
SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. WeAreCAS is an independent community site and is not affiliated with SAS Institute Inc.