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Singular spectrum analysisusing R /

Hassani, Hossein.

Singular spectrum analysisusing R /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Singular spectrum analysisby Hossein Hassani, Rahim Mahmoudvand.
其他題名:	using R /
作者:	Hassani, Hossein.
其他作者:	Mahmoudvand, Rahim.
出版者:	London :Palgrave Macmillan UK :2018.
面頁冊數:	xiii, 149 p. :digital ;24 cm.
Contained By:	Springer eBooks
標題:	Time-series analysisComputer programs.
電子資源:	http://dx.doi.org/10.1057/978-1-137-40951-5
ISBN:	9781137409515$q(electronic bk.)

Singular spectrum analysisusing R /
Hassani, Hossein.

Singular spectrum analysisusing R /[electronic resource] :by Hossein Hassani, Rahim Mahmoudvand. - London :Palgrave Macmillan UK :2018. - xiii, 149 p. :digital ;24 cm. - Palgrave advanced texts in econometrics. - Palgrave advanced texts in econometrics..

Preface -- 1. Univariate Singular Spectrum Analysis -- 2. Multivariate Singular Spectrum Analysis -- 3. Applications of Singular Spectrum Analysis -- 4. More on Filtering and Forecasting by SSA -- A. A Short Introduction to R -- B. Theoretical explanations.

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.

ISBN: 9781137409515$q(electronic bk.)

Standard No.: 10.1057/978-1-137-40951-5doiSubjects--Topical Terms:

247656
Time-series analysis
--Computer programs.

LC Class. No.: QA280 / .H377 2018

Dewey Class. No.: 519.55028551

Singular spectrum analysisusing R /
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520 $a 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.
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