Singular Spectrum Analysis

1. Front Matter

   Pages i-xiii

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2. Univariate Singular Spectrum Analysis

   • Hossein Hassani, Rahim Mahmoudvand

   Pages 1-48

3. Multivariate Singular Spectrum Analysis

   • Hossein Hassani, Rahim Mahmoudvand

   Pages 49-86

4. Applications of Singular Spectrum Analysis

   • Hossein Hassani, Rahim Mahmoudvand

   Pages 87-101

5. More on Filtering and Forecasting by SSA

   • Hossein Hassani, Rahim Mahmoudvand

   Pages 103-115

6. Back Matter

   Pages 117-149

   PDF

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.  





                          


            

• data analysis
• statistics
• time series analysis
• time series data
• non-parametric technique
• singular spectrum analysis (SSA)
• The R system

     

• Research Institute of Energy Management and Planning, University of Tehran, Tehran, Iran

  Hossein Hassani

• Department of Statistics, Bu-Ali Sina University, Hamedan, Iran

  Rahim Mahmoudvand

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.   





                   
               

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