Table of contents

  1. Front Matter
    Pages i-xiii
  2. Hossein Hassani, Rahim Mahmoudvand
    Pages 1-48
  3. Hossein Hassani, Rahim Mahmoudvand
    Pages 49-86
  4. Hossein Hassani, Rahim Mahmoudvand
    Pages 87-101
  5. Hossein Hassani, Rahim Mahmoudvand
    Pages 103-115
  6. Back Matter
    Pages 117-149

About this book


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

Authors and affiliations

  • Hossein Hassani
    • 1
  • Rahim Mahmoudvand
    • 2
  1. 1.Research Institute of Energy Management and PlanningUniversity of TehranTehranIran
  2. 2.Department of StatisticsBu-Ali Sina UniversityHamedanIran

Bibliographic information