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Book cover Singular Spectrum Analysis for Time Series

Part of the book series: SpringerBriefs in Statistics ((BRIEFSSTATIST))

Abstract

Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting. It combines elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing.

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Notes

  1. 1.

    In the literature on SSA, Basic SSA is sometimes called BK SSA and what we call ‘Toeplitz SSA’ is called VG SSA; here BK and VG stand for Broomhead & King [4, 5] and Vautard & Ghil [32], respectively.

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Authors and Affiliations

  1. Mathematics, St. Petersburg University, Universitetsky pr. 28, 198504, St. Petersburg, Russia

    Nina Golyandina

  2. School of Mathematics, Cardiff University, Senghennydd Rd., CF24 4AG, Cardiff, United Kingdom

    Anatoly Zhigljavsky

Authors
  1. Nina Golyandina
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  2. Anatoly Zhigljavsky
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Correspondence to Nina Golyandina .

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Golyandina, N., Zhigljavsky, A. (2013). Introduction. In: Singular Spectrum Analysis for Time Series. SpringerBriefs in Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34913-3_1

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