Overview
- Presents a detailed, almost encyclopedic account of nonlinear time series analysis
- Shows concrete applications of modern nonlinear time series analysis on a variety of empirical time series, with a liberal use of color graphics
- Provides a toolbox of discrete-time nonlinear models, methods, tests and concepts
- Includes supplementary material: sn.pub/extras
- Request lecturer material: sn.pub/lecturer-material
Part of the book series: Springer Series in Statistics (SSS)
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Table of contents (12 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods.
The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods.
To make the book as user friendly as possible, major supporting concepts and specialized tables are appended at the end of every chapter. In addition, each chapter concludes with a set of key terms and concepts, as well as a summary of the main findings. Lastly, the book offers numerous theoretical and empirical exercises, with answers provided by the author in an extensive solutions manual.
Reviews
“This is an excellent addition to the library of books on time series analysis. The most attractive feature of this book is that it places importance on developing intuition about nonlinear time series rather than the more formal theorem-proof approach. It is abundant with data examples and simulations that enhance understanding of the stochastic properties of the models. In my opinion, the approach taken is the best pedagogical technique to learn about time series models.” (Hernando Ombao, Journal of the American Statistical Association JASA, Vol. 113 (522), 2018)
“For the scientific quality of its content I do not exaggerate if I consider this book as a treasure.” (Oscar Busto, zbMATH 1376.62001, 2018)
Authors and Affiliations
About the author
Jan G. De Gooijer is Emeritus Professor of Economic Statistics at the University of Amsterdam. He completed an M.Sc. degree in mathematical statistics at Delft Technical University and a Ph.D. in economics at the Vrije Universiteit (“Free University”) Amsterdam. He has (co-)authored over 100 publications on forecasting, time series analysis, econometrics, and statistics. Jan has been Associate Editor, Editor and Editor-in-Chief of The International Journal of Forecasting, Associate Editor of the Journal of Forecasting, and he has served on the editorial board of Empirical Economics. He is an elected member of the International Statistical Institute, and an Honorary Fellow of the International Institute of Forecasters. He has held visiting professor positions at the Universities of Umeå (Sweden), British Columbia (Canada) and Montpellier II (France), as well as Royal Holloway College (London, UK).
Bibliographic Information
Book Title: Elements of Nonlinear Time Series Analysis and Forecasting
Authors: Jan G. De Gooijer
Series Title: Springer Series in Statistics
DOI: https://doi.org/10.1007/978-3-319-43252-6
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2017
Hardcover ISBN: 978-3-319-43251-9Published: 07 April 2017
Softcover ISBN: 978-3-319-82770-4Published: 18 July 2018
eBook ISBN: 978-3-319-43252-6Published: 30 March 2017
Series ISSN: 0172-7397
Series E-ISSN: 2197-568X
Edition Number: 1
Number of Pages: XXI, 618
Number of Illustrations: 95 illustrations in colour
Topics: Statistical Theory and Methods, Statistics for Life Sciences, Medicine, Health Sciences, Statistics for Business, Management, Economics, Finance, Insurance, Applications of Nonlinear Dynamics and Chaos Theory