Singular Spectrum Analysis: Using R (Palgrave Advanced Texts in Econometrics) - Hardcover

Hassani, Hossein; Mahmoudvand, Rahim

Hardcover

ISBN 10: 1137409509 ISBN 13: 9781137409508

Publisher: Palgrave Pivot, 2018

Synopsis

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.  

                          

            

About this title

About the Author

Dr. Hossein Hassani is Associate Professor at the University of Tehran, Iran, specialising in Singular Spectrum Analysis (SSA) and its applications, particularly in analyzing and forecasting complex time series with various structures. He is a published author/co-author with over 100 journal articles and 6 book titles including Singular Spectrum Analysis of Biomedical Signals. 

Dr. Rahim Mahmoudvand is Assistant Professor at Bu-Ali Sina University, Iran. He serves as a member of the editorial board for international journals and is currently a council member of the International Society for Business and Industrial Statistics. His current research interests include singular spectrum analysis, actuarial sciences and applied statistics.   

                   

               

From the Back Cover

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.  

Edition details

• Publisher: Palgrave Pivot
• Publication date: 2018
• Language: English
• ISBN 10: 1137409509
• ISBN 13: 9781137409508
• Binding: Hardcover
• Edition number: 1
• Number of pages: 162