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SpringerBriefs in Statistics

Singular Spectrum Analysis for Time Series

Authors: Golyandina, Nina, Zhigljavsky, Anatoly

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  • Presents the methodology of Singular Spectrum Analysis (SSA)
  • Describes  Multivariate Singular Spectrum Analysis (MSSA) and SSA for image processing (2D-SSA) 
  • Illustrated with examples and case studies
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eBook 42,79 €
price for France (gross)
  • ISBN 978-3-662-62436-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 52,74 €
price for France (gross)
About this book

This book gives an overview of singular spectrum analysis (SSA). SSA is a technique of time series analysis and forecasting  combining  elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. 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. Rapidly  increasing number of novel applications of SSA is a consequence of the  new  fundamental research on SSA and  the recent progress in  computing and software engineering which  made it possible to use SSA for very complicated tasks that were unthinkable  twenty years ago. In this book, the methodology of SSA is concisely  but at the same time comprehensively explained by  two  prominent statisticians with huge experience in SSA. The book offers a valuable resource for a very wide readership, including professional statisticians, specialists in signal and image processing, as well as specialists in numerous applied disciplines interested in using statistical methods for time series analysis, forecasting, signal and image processing. The second edition of the book contains many updates and some new material including a thorough discussion on  the place of SSA among other methods and new sections on multivariate and multidimensional extensions of  SSA.

About the authors

Nina Golyandina received her MSc and PhD degrees in mathematics at St.Petersburg State University, Russia, in 1985 and 1998, respectively. She started to work at St.Petersburg State University in 1985, where she is currently an Associate Professor of Statistical Modelling Department, Faculty of Mathematics and Mechanics. Her main areas of research interest are statistical modeling and applied statistics, especially time series investigation by means of singular spectrum analysis.  Dr. Golyandina is the coauthor of three monographs on singular spectrum analysis and of more than 30 research papers in refereed journals related to applied probability and statistics. During last twenty years, she was involved in different projects related to singular spectrum analysis.

 Anatoly Zhigljavsky has received his BSc, MSc and PhD degrees in mathematics and statistics at Faculty of Mathematics, St.Petersburg State University. He became professor of statistics at the St.Petersburg State University in 1989. Since 1997 he is a professor, Chair in Statistics at Cardiff University.  Anatoly Zhigljavsky is the author or co-author of 10 monographs on the topics of time series analysis, stochastic global optimization, optimal experimental design and dynamical systems; he is the editor/co-editor of 9 books on various topics and the author of more than 150 research papers in refereed journals. He has organized several major conferences on time series analysis, experimental design and global optimization. In 2019, he has received a prestigious Constantine Caratheodory award by the International Society for Global Optimization for his  contribution to  stochastic optimization.

Table of contents (3 chapters)

Table of contents (3 chapters)

Buy this book

eBook 42,79 €
price for France (gross)
  • ISBN 978-3-662-62436-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 52,74 €
price for France (gross)
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Bibliographic Information

Bibliographic Information
Book Title
Singular Spectrum Analysis for Time Series
Authors
Series Title
SpringerBriefs in Statistics
Copyright
2020
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature
eBook ISBN
978-3-662-62436-4
DOI
10.1007/978-3-662-62436-4
Softcover ISBN
978-3-662-62435-7
Series ISSN
2191-544X
Edition Number
2
Number of Pages
IX, 146
Number of Illustrations
6 b/w illustrations, 38 illustrations in colour
Topics