The SAS Data Science Blog
Advanced analytics from SAS data scientists
Enforce SAS code standards using SASjs and GitHub Actions to maintain secure, readable, and maintainable code. Automated linting blocks non-compliant code from merging into protected branches.
Accurately identifying lag structures between related time series is essential in public health forecasting, particularly during epidemics where delays between infections and hospitalizations affect planning. Using a simulated SEIR model and SAS Viya’s PROC TSSELECTLAG, distance correlation is shown to outperform Pearson correlation by correctly identifying nonlinear lag relationships—such as the true seven-day lag between new infections and hospital admissions.
As agentic AI systems evolve through protocols like MCP and A2A, traditional security practices must be adapted to address new risks such as goal misalignment and tool instruction abuse. This article explores practical threat modeling strategies, including goal alignment cascades and distinguishing between parameter-only vs. instruction-enabled tool calls.
Get an introduction to AI Copilot for the SAS Strategic Supply Chain Optimization Model, designed to democratize access to advanced modeling capabilities.
SAS's Kevin Scott explains how to set up and analyze a dataset for forecasting in SAS Viya with a particular emphasis on selecting lags for dynamic models
Learn how to incorporate operational variables, or covariates, into predicting asset survival probabilities.