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Singular Spectrum Analysis for Time Series

Part of the SpringerBriefs in Statistics Book Series

DOI: 10.1007/978-3-662-62436-4

ISBN: 978-3-662-62435-7

Publisher: Springer Berlin Heidelberg - Springer Journals

Nov 24, 2020

Available

Introduction

Golyandina, Nina; Zhigljavsky, Anatoly

Pages: 1 –20

[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...
Available

Basic SSA

Golyandina, Nina; Zhigljavsky, Anatoly

Pages: 21 –90

[In Chap. 2, SSA is normally considered as a model-free technique. The main body of Chap. 2 is devoted to careful description of Basic SSA, its main capabilities, choice of parameters and various indicators which help in recognizing good separability between different components and hence...
Available

SSA for Forecasting, Interpolation, Filtering and Estimation

Golyandina, Nina; Zhigljavsky, Anatoly

Pages: 91 –146

[The applications of SSA dealt with in Chap. 3 require the use of models and hence SSA of Chap. 3 is mostly model-based. As the main model, the assumption that the components of the original time series, which are extracted by SSA, satisfy (at least, locally) certain linear recurrence relations....

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