| 书目名称 | Singular Spectrum Analysis with R | | 编辑 | Nina Golyandina,Anton Korobeynikov,Anatoly Zhiglja | | 视频video | | | 概述 | 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 packa | | 丛书名称 | Use R! | | 图书封面 |  | | 描述 | .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 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 | | 出版日期 | Book 2018 | | 关键词 | 37M10, 68U10; forecasting; signal processing; singular spectrum analysis; singular value decomposition; t | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-662-57380-8 | | isbn_softcover | 978-3-662-57378-5 | | isbn_ebook | 978-3-662-57380-8Series ISSN 2197-5736 Series E-ISSN 2197-5744 | | issn_series | 2197-5736 | | copyright | Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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发表于 2025-3-21 18:10:26
