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Singular Spectrum Analysis for Time SeriesIntroduction

Singular Spectrum Analysis for Time Series: Introduction [Chapter 1 provides an overview of SSA methodology, outlines the structure of the book and examines the place of SSA among other techniques of time series analysis and signal processing. The R-based package Rssa, a powerful and comprehensive implementation of SSA-related techniques, is introduced. A list of the main symbols and several historical and bibliographical remarks conclude Chap. 1.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Singular Spectrum Analysis for Time SeriesIntroduction

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Publisher
Springer Berlin Heidelberg
Copyright
© The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature 2020
ISBN
978-3-662-62435-7
Pages
1 –20
DOI
10.1007/978-3-662-62436-4_1
Publisher site
See Chapter on Publisher Site

Abstract

[Chapter 1 provides an overview of SSA methodology, outlines the structure of the book and examines the place of SSA among other techniques of time series analysis and signal processing. The R-based package Rssa, a powerful and comprehensive implementation of SSA-related techniques, is introduced. A list of the main symbols and several historical and bibliographical remarks conclude Chap. 1.]

Published: Nov 24, 2020

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