A Human Generated Introduction to Generative AI, Part 1: Synthetic Data Generation
Recent Library Articles
Recently in the SAS Community Library: In the first of two posts on applications of generative AI, SAS' @JThompson reveals the role of generating synthetic data.
I am performing simple Pearson, Spearman and Kendall correlations between many variables using PROC CORR. 1. I need to suppress non-significant correlations (p > 0.05) in my matrix, leaving only significant correlations (p <0.05). 2. I need to show confidence intervals for these correlations. How can I do this? Thanks!
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A new update is available for SAS Model Implementation Platform , version 3.2 : Hot Fix: F6U010 - Published 16MAY2025 , Download link for F6U010 Component name: SAS Model Implementation Platform Related SAS release: SAS 9.4 Issues addressed in F6U010 SAS Note 64760 An "Unable to Load Published Modeling System" error occurs when importing a SAS® Model Implementation Platform export or modeling system file SAS Note 64919 Added functionality to SAS® Model Implementation Platform to support maximum horizon of 0 for specific runs SAS Note 69824 You encounter time-out issues in the HTML Commons' session REST API and in SAS® Risk web applications' sessions This list of notes might be incomplete. For a complete list of issues addressed by this hot fix, visit the hot fix page for F6U010 Note: A comprehensive list of all SAS hot fixes is available from support.sas.com. You can use the SAS Hot Fix Analysis, Download, and Deployment (SASHFADD) tool to manage your SAS hot fixes.
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SAS Viya supports REST API that can help accomplish various tasks from data management to model scoring.
As of the Stable 2025.04 release, you can also create and manipulate SAS Visual Analytics reports using REST API. REST API make it:
Easy to automate repeated tasks.
Possible to schedule various tasks.
In this post, we will learn:
how to use SAS Viya REST API
how to create a report while adding a data source
what ETags are
modify data item properties in an existing report
check if an object already exists in a report
how to add objects to an existing report
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The behaviour of the JES API appears to have changed in the last year or so, and we need some help getting our (previously functional) code to work!
We are running a Job (using POST /jobExecution/jobs - https://developer.sas.com/rest-apis/jobExecution/createJob ) that returns a JSON file generated using the following code (as described here )
filename _webout filesrvc parenturi="&SYS_JES_JOB_URI" name="_webout.json";
data _null_;
file _webout;
put '{"name" : "value")';
run;
The exact API request looks like this:
With the following payload:
We then poll for results using: /jobExecution/jobs/db8810ec-7282-4093-a0f9-41f693ebf359/state?_action=wait&wait=300
And finally fetch the results using: /jobExecution/jobs/db8810ec-7282-4093-a0f9-41f693ebf359
With the following response:
We have tried tweaking the arguments, to no avail.
The _webout fileref is definitely created. We have also tried using the RESULTFILE option.
How to get the _webout result location returned to the JES API triggered Job?
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I have a electricity consumption daily time series. Data are from the last 3 years. I have adjusted a (0,1,1) model after difference (1) the log transformed series. (checked stationarity). I have identified some outliers but any of them resulted significant when I included it as regressors. It seems that there is not autocorrelation in the residuals (tests OK) but the heteroscedasticity tests are not fulfilled. Tried to model the residuals with arch models but cannot fix the problem of heteroscedasticity (conditional and unconditional). Any alternatives? proc arima data=work.series; identify var=lvalor(1) stationarity=(dickey) nlag=30; estimate p=(1) q=(1) noint method=ml; *outlier maxnum=5 alpha=0.01 id=fecha; forecast id=fecha interval=day out=b; run; quit; proc model data=b; parms const; residual = const ; fit residual / white breusch=(1 time); run; quit; proc autoreg data=b; model residual= / garch=(Q=2, p=2) maxit=50; output out=out R=pepe; run;
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