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Singular Spectrum Analysis

Using R

  • Book
  • © 2018

Overview

Authors:
  1. Hossein Hassani

    1. Research Institute of Energy Management and Planning, University of Tehran, Tehran, Iran

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    You can also search for this author in PubMed   Google Scholar

  2. Rahim Mahmoudvand

    1. Department of Statistics, Bu-Ali Sina University, Hamedan, Iran

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Fills an existing gap in the market
  • Details the theoretical aspects underlying SSA
  • Uniquely allows the user to apply the theory in practice using R software (which is freely available)

Part of the book series: Palgrave Advanced Texts in Econometrics (PATEC)

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Table of contents (4 chapters)

  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
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Keywords

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.  





                          


            

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Authors and Affiliations

  • 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

About the authors

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.   





                   
               

Bibliographic Information

  • Book Title: Singular Spectrum Analysis

  • Book Subtitle: Using R

  • Authors: Hossein Hassani, Rahim Mahmoudvand

  • Series Title: Palgrave Advanced Texts in Econometrics

  • DOI: https://doi.org/10.1057/978-1-137-40951-5

  • Publisher: Palgrave Pivot London

  • eBook Packages: Economics and Finance, Economics and Finance (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s) 2018

  • Hardcover ISBN: 978-1-137-40950-8Published: 12 July 2018

  • eBook ISBN: 978-1-137-40951-5Published: 25 June 2018

  • Series ISSN: 2662-639X

  • Series E-ISSN: 2662-6403

  • Edition Number: 1

  • Number of Pages: XIII, 149

  • Number of Illustrations: 40 b/w illustrations

  • Topics: Economics, general

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