Elements of Nonlinear Time Series Analysis and Forecasting (eBook)
XXI, 618 Seiten
Springer International Publishing (Verlag)
978-3-319-43252-6 (ISBN)
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.
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).
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).
Erscheint lt. Verlag | 30.3.2017 |
---|---|
Reihe/Serie | Springer Series in Statistics | Springer Series in Statistics |
Zusatzinfo | XXI, 618 p. 95 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Themenwelt | Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik |
Medizin / Pharmazie ► Allgemeines / Lexika | |
Naturwissenschaften ► Physik / Astronomie | |
Technik | |
Wirtschaft | |
Schlagworte | AR-GARCH model • ARMA model • frequency domain tests • high dimensional tests • Model Selection • nonlinear time series • nonparametric forecasting • tests for serial independence • time-domain linearity test |
ISBN-10 | 3-319-43252-4 / 3319432524 |
ISBN-13 | 978-3-319-43252-6 / 9783319432526 |
Haben Sie eine Frage zum Produkt? |
Größe: 14,8 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich