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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 different versions of SSA into a single tool, (c) shows the diverse tasks that SSA can be used for, (d) formally describes the main SSA methods and algorithms, and (e) provides tutorials on the Rssa package and the use of 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 book is written on a level accessible to a broad audience and includes a wealth of examples; hence it can also be used as a textbook for undergraduate and postgraduate courses on time series analysis and signal processing.
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 different versions of SSA into a single tool, (c) shows the diverse tasks that SSA can be used for, (d) formally describes the main SSA methods and algorithms, and (e) provides tutorials on the Rssa package and the use of 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 book is written on a level accessible to a broad audience and includes a wealth of examples; hence it can also be used as a textbook for undergraduate and postgraduate courses on time series analysis and signal processing.
Anton Korobeynikov received his MSc and PhD degrees in applied mathematics from St. Petersburg State University, Russia, in 2007 and 2010, respectively. He began working at St. Petersburg State University in 2007, where he currently holds the position of Associate Professor of Statistical Modeling. Dr. Korobeynikov's main research interests include computational and appliedstatistics, including time series analysis, efficient implementation of algorithms of computational statistics, and probabilistic methods in bioinformatics. He is the original author of the R-package Rssa for singular spectrum analysis.
Anatoly Zhigljavsky graduated from the Faculty of Mathematics, St. Petersburg State University, in 1976. He received his PhD in applied probability in 1981 and was a Professor of Statistics at the same university from 1989 to 1997. Since 1997 he has been a Professor and Chair of Statistics at Cardiff University. Anatoly Zhigljavsky is the author or co-author of 9 monographs on the topics of SSA for time series analysis, stochastic global optimization, optimal experimental design and dynamical systems; he is the editor/co-editor of 8 books on various topics and the author of over 150 research papers in peer-reviewed journals. He has organized several major conferences on time series analysis, experimental design and global optimization, and serves on the editorial board of two journals: Journal of Global Optimization, and Statistics and Its Interface. He is also the director of the Centre for Optimisation and Its Applications at Cardiff University.
Presents an up-to-date overview of Singular Spectrum Analysis (SSA) methodology
Demonstrates how SSA can be used for the analysis of time series and digital images
Provides tutorials on the Rssa package
Illustrated with real-life examples
| Erscheinungsjahr: | 2018 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Reihe: | Use R! |
| Inhalt: |
xiii
272 S. 15 s/w Illustr. 106 farbige Illustr. 272 p. 121 illus. 106 illus. in color. |
| ISBN-13: | 9783662573785 |
| ISBN-10: | 3662573784 |
| Sprache: | Englisch |
| Herstellernummer: | 978-3-662-57378-5 |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Golyandina, Nina
Zhigljavsky, Anatoly Korobeynikov, Anton |
| Auflage: | 1st ed. 2018 |
| Hersteller: |
Springer-Verlag GmbH
Springer Berlin Heidelberg Use R! |
| Maße: | 235 x 155 x 16 mm |
| Von/Mit: | Nina Golyandina (u. a.) |
| Erscheinungsdatum: | 25.06.2018 |
| Gewicht: | 0,441 kg |
Anton Korobeynikov received his MSc and PhD degrees in applied mathematics from St. Petersburg State University, Russia, in 2007 and 2010, respectively. He began working at St. Petersburg State University in 2007, where he currently holds the position of Associate Professor of Statistical Modeling. Dr. Korobeynikov's main research interests include computational and appliedstatistics, including time series analysis, efficient implementation of algorithms of computational statistics, and probabilistic methods in bioinformatics. He is the original author of the R-package Rssa for singular spectrum analysis.
Anatoly Zhigljavsky graduated from the Faculty of Mathematics, St. Petersburg State University, in 1976. He received his PhD in applied probability in 1981 and was a Professor of Statistics at the same university from 1989 to 1997. Since 1997 he has been a Professor and Chair of Statistics at Cardiff University. Anatoly Zhigljavsky is the author or co-author of 9 monographs on the topics of SSA for time series analysis, stochastic global optimization, optimal experimental design and dynamical systems; he is the editor/co-editor of 8 books on various topics and the author of over 150 research papers in peer-reviewed journals. He has organized several major conferences on time series analysis, experimental design and global optimization, and serves on the editorial board of two journals: Journal of Global Optimization, and Statistics and Its Interface. He is also the director of the Centre for Optimisation and Its Applications at Cardiff University.
Presents an up-to-date overview of Singular Spectrum Analysis (SSA) methodology
Demonstrates how SSA can be used for the analysis of time series and digital images
Provides tutorials on the Rssa package
Illustrated with real-life examples
| Erscheinungsjahr: | 2018 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Reihe: | Use R! |
| Inhalt: |
xiii
272 S. 15 s/w Illustr. 106 farbige Illustr. 272 p. 121 illus. 106 illus. in color. |
| ISBN-13: | 9783662573785 |
| ISBN-10: | 3662573784 |
| Sprache: | Englisch |
| Herstellernummer: | 978-3-662-57378-5 |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Golyandina, Nina
Zhigljavsky, Anatoly Korobeynikov, Anton |
| Auflage: | 1st ed. 2018 |
| Hersteller: |
Springer-Verlag GmbH
Springer Berlin Heidelberg Use R! |
| Maße: | 235 x 155 x 16 mm |
| Von/Mit: | Nina Golyandina (u. a.) |
| Erscheinungsdatum: | 25.06.2018 |
| Gewicht: | 0,441 kg |
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