 Название: Singular Spectrum Analysis: Using R
Автор: Hossein Hassani, Rahim Mahmoudvand
Издательство: Palgrave
ISBN: 978-1-137-40950-8
Год: 2018
Страниц: 158
Язык: английский
Формат: pdf (true), mobi, epub
Размер: 11.09 MB
This book provides a broad introduction to computational aspects of Singular Spectrum Analysis (SSA) which is a non-parametric technique and requires no prior assumptions such as stationarity, normality or linearity of the series. This book is unique as it not only details the theoretical aspects underlying SSA, but also provides a comprehensive guide enabling the user to apply the theory in practice using the R software.
Further, it provides the user with step- by- step coding and guidance for the practical application of the SSA technique to analyze their time series databases using R. The first two chapters present basic notions of univariate and multivariate SSA and their implementations in R environment. The next chapters discuss the applications of SSA to change point detection, missing-data imputation, smoothing and filtering. This book is appropriate for researchers, upper level students (masters level and beyond) and practitioners wishing to revive their knowledge of times series analysis or to quickly learn about the main mechanisms of SSA.
R is a programme which allows the user to create their own objects, functions and packages. The R system is command driven and it documents the analysis steps making it easy to reproduce or update the analysis and figure errors. R can be installed on any platform and is license free. A major advantage with R is that it allows integrating and interacting with other paid platforms such as SAS, Stata, SPSS and Minitab. Although there are some books in the market relating to SSA, this book is unique as it not only details the theoretical aspects underlying SSA, but also provides a comprehensive guide enabling the user to apply the theory in practice using the R software. This book provides the user with step-by-step coding and guidance for the practical application of the SSA technique to analyse their time series databases using R. We provided some basic R commands in Appendix, so the readers who are not familiar with this language please learn the very basics in the Appendix at first.
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