Mathematical optimization for time series decomposition
Type :
Article
Publication Status :
Published
Access :
restrictedAccess
Abstract
Decomposing time series into trend and seasonality components reveals insights used in forecasting and anomaly detection. This study proposes a mathematical optimization approach that addresses several data-related issues in time series decomposition. Our approach does not only handle longer and multiple seasons but also identifies outliers and trend shifts. Numerical experiments on real-world and synthetic problem sets present the effectiveness of the proposed approach.
Source :
OR Spectrum
Date :
2021-09
Volume :
43
Issue :
3
Publisher :
Springer
Collections
Share this page