Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/28715
Title: | Time Series components separation based on Singular Spectral Analysis visualization: an HJ-biplot method application |
Author: | Silva, Alberto Oliveira da Freitas, Adelaide |
Keywords: | Singular Spectrum Analysis NIPALS algorithm Biplots |
Issue Date: | Jun-2020 |
Publisher: | International Academic Press |
Abstract: | The extraction of essential features of any real-valued time series is crucial for exploring, modeling and producing, for example, forecasts. Taking advantage of the representation of a time series data by its trajectory matrix of Hankel constructed using Singular Spectrum Analysis, as well as of its decomposition through Principal Component Analysis via Partial Least Squares, we implement a graphical display employing the biplot methodology. A diversity of types of biplots can be constructed depending on the two matrices considered in the factorization of the trajectory matrix. In this work, we discuss the called HJ-biplot which yields a simultaneous representation of both rows and columns of the matrix with maximum quality. Interpretation of this type of biplot on Hankel related trajectory matrices is discussed from a real-world data set. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/28715 |
DOI: | 10.19139/soic-2310-5070-897 |
ISSN: | 2311-004X |
Publisher Version: | http://www.iapress.org/index.php/soic/article/view/897 |
Appears in Collections: | CIDMA - Artigos DMat - Artigos PSG - Artigos |
Files in This Item:
File | Description | Size | Format | |
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2020SilvaEFreitas_Time Series components separation based on Singular Spectral Analysis.pdf | 200.51 kB | Adobe PDF | View/Open |
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