Singular Spectrum Analysis with R. 1st ed. 2018

種類:

電子ブック

責任表示:

by Nina Golyandina, Anton Korobeynikov, Anatoly Zhigljavsky

出版情報:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2018

著者名:

• Golyandina, Nina.
• Korobeynikov, Anton.
• Zhigljavsky, Anatoly.
• SpringerLink (Online service)

シリーズ名:

Use R! ;

ISBN:

9783662573808 [3662573806]    

注記:

Preface -- Common symbols and acronyms -- Contents -- 1 Introduction: Overview -- 2 SSA analysis of one-dimensional time series -- 3 Parameter estimation, forecasting, gap filling -- 4 SSA for multivariate time series -- 5 Image processing -- Index -- References.
This comprehensive and richly illustrated volume provides up-to-date material on Singular Spectrum Analysis (SSA). SSA is a well-known methodology for the analysis and forecasting of time series. Since quite recently, SSA is also being used to analyze digital images and other objects that are not necessarily of planar or rectangular form and may contain gaps. SSA is multi-purpose and naturally combines both model-free and parametric techniques, which makes it a very special and attractive methodology for solving a wide range of problems arising in diverse areas, most notably those associated with time series and digital images. An effective, comfortable and accessible implementation of SSA is provided by the R-package Rssa, which is available from CRAN and reviewed in this book. Written by prominent statisticians who have extensive experience with SSA, the book (a) presents the up-to-date SSA methodology, including multidimensional extensions, in language accessible to a large circle of users, (b) combines di

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