You'll want to make time for this SAS Talks Webinar, where SAS® expert David Corliss shows you how to apply cluster analysis methodology to time series data.
Segments are often identified using static characteristics, but evolving systems may be better described by how things change over time. See a demonstration with examples from many industries. No prior experience with clustering analysis is needed – but intermediate SAS programmers will benefit the most from this discussion.
- Learn how to apply standard SAS clustering procedures (Base SAS and SAS/STAT®) to time series data.
- Understand how to use this method to identify phases or stages of development in systems that change over time.
- See a demonstration of the analysis of seasonal changes in gas prices.
- Hear about examples of dynamic systems analysis in biostatistics, econometrics, meteorology and astrophysics.
David J. Corliss, PhD
Manager, Emerging Technologies
Magnify Analytic Solutions
David Corliss has been using SAS since 1994. He leads the analytics R&D team at Magnify Analytic Solutions in Detroit and is a part-time faculty member in astronomy at Wayne State University. His recent work has focused on bringing university research on time series analysis to the wider SAS audience. He is a regular speaker at SAS Global Forum as well as local and regional events. Corliss is active in the Michigan SAS Users Group and MidWest SAS Users Group, regularly serving as a section chair at regional events. This webinar grew out of his 2012 SAS Global Forum presentation, which won Best Contributed Paper in Statistics and Data Analysis. Corliss holds a PhD in statistical astrophysics.