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Singular spectrum analysis for time series

Author: Nina Golyandina; A A Zhigli︠a︡vskiĭ
Publisher: Heidelberg : Springer, [2013] ©2013
Series: SpringerBriefs in statistics.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical  Read more...

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Document Type: Book
All Authors / Contributors: Nina Golyandina; A A Zhigli︠a︡vskiĭ
ISBN: 9783642349126 3642349129
OCLC Number: 837505932
Description: vii, 119 pages : illustrations (some color) ; 23 cm.
Contents: Introduction: Preliminaries.- SSA Methodology and the Structure of the Book.- SSA Topics Outside the Scope of this Book.- Common Symbols and Acronyms.- Basic SSA: The Main Algorithm.- Potential of Basic SSA.- Models of Time Series and SSA Objectives.- Choice of Parameters in Basic SSA.- Some Variations of Basic SSA.- SSA for Forecasting, interpolation, Filtration and Estimation: SSA Forecasting Algorithms.- LRR and Associated Characteristic Polynomials.- Recurrent Forecasting as Approximate Continuation.- Confidence Bounds for the Forecast.- Summary and Recommendations on Forecasting Parameters.- Case Study: `Fortified Wine'.- Missing Value Imputation.- Subspace-Based Methods and Estimation of Signal Parameters.- SSA and Filters.
Series Title: SpringerBriefs in statistics.
Responsibility: Nina Golyandina, Anatoly Zhigljavsky.

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From the reviews:"This book is fully devoted to the methodology of a technique for time series analysis and forecasting called singular spectrum analysis (SSA). ... The authors of the book are Read more...

 
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