Hidden Markov models
Provides powerful HMM procedure for modeling and predicting hidden Markov models.
Run large-scale, multivariate simulations that you can fit using different specifications. Perform count regression, cross-sectional analysis, panel data analysis and censored event estimation for both discrete and continuous events. The SAS® Viya® scalable, distributed in-memory engine delivers econometric modeling results on even the largest data sets at exceptional processing speeds. And in-memory data persistence eliminates the need to load data multiple times during iterative analyses.
Python, Java, R and Lua programmers can experience the power of SAS Econometrics without having to learn SAS. The SAS Viya engine enables programmers to access powerful, trusted and tested SAS algorithms from their preferred coding environment.
Understand how varying economic and market conditions, customer demographics, pricing decisions, marketing activities and more can affect your business. Analyze risks, and respond to regulatory requirements. The solution enables you to model and simulate any business process, no matter how complex – even when time dependencies, simultaneous relationships or dynamic processes complicate the analyses. By combining forecasting processes with econometric analysis, you can proactively shape a more profitable future.
This solution runs on SAS® Viya®, which has the breadth and depth to conquer any analytics challenge, from experimental to mission critical. SAS Viya extends the SAS Platform to enable everyone – data scientists, business analysts, developers and executives alike – to collaborate and realize innovative results faster.
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