Business Knowledge Series course
Presented by Terry Woodfield, Ph.D., Analytical Training Consultant, Education Division, SAS
This class teaches how to model, interpret, and predict time series data using UCMs. The UCM procedure analyzes and forecasts equally spaced univariate time series data using the Unobserved Components Models (UCM).
Learn how to
- analyze time series data using a novel class of models called the Unobserved Component Models (UCM). The UCMs decompose the response series into components such as trend, seasonals, cycles, and the regression effects due to predictor series.
- use the UCM procedure to find a suitable model for the series of interest, to obtain extensive model diagnostics, and to generate series forecasts and the forecasts of the constituent components
- get detailed understanding of the series dynamics by analyzing the plots of the estimated components.
Who should attend
Those who want to analyze time series data to uncover patterns such as trend, seasonal effects, and cycles using the latest techniques
Before attending this course, you should
- have experience with regression modeling
- be familiar with at least one time series modeling technique, such as Box and Jenkins or exponential smoothing
- some familiarity with SAS software.
This course addresses SAS/ETS software.