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Multivariate posterior singular spectrum analysis |
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| Author: | Launonen, Ilkka1; Holmström, Lasse1 |
| Organizations: |
1Department of Mathematical Sciences, University of Oulu, Oulu, Finland |
| Format: | article |
| Version: | accepted version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 1.5 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe2019041011866 |
| Language: | English |
| Published: |
Springer Nature,
2017
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| Publish Date: | 2017-10-27 |
| Description: |
AbstractA generalized, multivariate version of the Posterior Singular Spectrum Analysis (PSSA) method is described for the identification of credible features in multivariate time series. We combine Bayesian posterior modeling with multivariate SSA (MSSA) and infer the MSSA signal components with a credibility analysis of the posterior sample. The performance of multivariate PSSA (MPSSA) is compared to the single-variate PSSA with an artificial example and the potential of MPSSA is demonstrated with real data using NAO and SOI climate index series. see all
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| Series: |
Statistical methods and applications |
| ISSN: | 1618-2510 |
| ISSN-E: | 1613-981X |
| ISSN-L: | 1618-2510 |
| Volume: | 26 |
| Issue: | 3 |
| Pages: | 361 - 382 |
| DOI: | 10.1007/s10260-016-0372-9 |
| OADOI: | https://oadoi.org/10.1007/s10260-016-0372-9 |
| Type of Publication: |
A1 Journal article – refereed |
| Field of Science: |
111 Mathematics 112 Statistics and probability |
| Subjects: | |
| Funding: |
Research supported by Academy of Finland Project No. 250862 and a grant from the Alfred Kordelin Foundation. |
| Academy of Finland Grant Number: |
250862 |
| Detailed Information: |
250862 (Academy of Finland Funding decision) |
| Copyright information: |
© Springer-Verlag Berlin Heidelberg 2016. This is a post-peer-review, pre-copyedit version of an article published in Stat Methods Appl. The final authenticated version is available online at: https://doi.org/10.1007/s10260-016-0372-9. |