The SAS Data Science Blog
Advanced analytics from SAS data scientists
Panel data are commonly used in today’s economics research. Panel data regression stands out as a powerful tool that aids in unraveling trends and patterns that evolve over time. This tool is particularly valuable when considering hidden factors in the investigations of cause-and-effect relationships. In this post, you will be
Learn how the %FiniteHMM macro can automatically pre-process input data as well as post-process output tables for finite Hidden Markov Models (HMMs) using PROC HMM.
SAS Model Manager and the sasctl packages aim to create a seamless ModelOps and MLOps process for Python and R models. Python and R models are not second-class citizens within SAS Model Manager. SAS, Python, and R models can be easily managed using our no-code/low-code interface. This is an interface that can be extended to support a variety of use cases.