| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6953060 | Journal of the Franklin Institute | 2018 | 27 Pages |
Abstract
Singular Spectrum Analysis (SSA) is a relatively simple and powerful method in the area of time series analysis that is mainly based on matrix analysis. In this paper, we present a methodological comparison between the univariate and multivariate versions of SSA. Additionally, we explore the advantages of multivariate SSA in terms of theoretical results and with application to a real data set on currency exchange rates.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Paulo Canas Rodrigues, Rahim Mahmoudvand,