Multivariate posterior singular spectrum analysis

Ilkka Launonen () and Lasse Holmström
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Ilkka Launonen: University of Oulu
Lasse Holmström: University of Oulu

Statistical Methods & Applications, 2017, vol. 26, issue 3, No 2, 382 pages

Abstract: Abstract A 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.

Keywords: Time series; SSA; Bayesian inference; Multivariate; Climate index (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10260-016-0372-9

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