Barucca, P;
Kieburg, M;
Ossipov, A;
(2020)
Eigenvalue and Eigenvector Statistics in Time Series Analysis.
EPL (Europhysics Letters)
, 129
(6)
, Article 60003. 10.1209/0295-5075/129/60003.
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Abstract
The study of correlated time-series is ubiquitous in statistical analysis, and the matrix decomposition of the cross-correlations between time series is a universal tool to extract the principal patterns of behavior in a wide range of complex systems. Despite this fact, no general result is known for the statistics of eigenvectors of the cross-correlations of correlated time-series. Here we use supersymmetric theory to provide novel analytical results that will serve as a benchmark for the study of correlated signals for a vast community of researchers.
| Type: | Article |
|---|---|
| Title: | Eigenvalue and Eigenvector Statistics in Time Series Analysis |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1209/0295-5075/129/60003 |
| Publisher version: | https://doi.org/10.1209/0295-5075/129/60003 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10074325 |
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