Advertisement
Published in:
2024 | OriginalPaper | Chapter
10. Explanatory Time Series Models
Author : Cynthia Fraser
Published in: Business Statistics for Competitive Advantage with Excel and JMP
Publisher: Springer Nature Switzerland
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
An explanatory model from time series data allows us to identify performance drivers and forecast performance given specific driver values, just as regression models from cross sectional data do. When decision makers want to forecast future performance in the shorter term, a time series of past performance is used to identify drivers and fit a model. A time series model can be used to identify drivers whose variation over time is associated with later variation in performance over time.