Description: Elements of Nonlinear Time Series Analysis and Forecasting, Hardcover by De Gooijer, Jan G., ISBN 3319432516, ISBN-13 9783319432519, Like New Used, Free shipping in the US
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.
Th 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 th 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, th offers numerous theoretical and empirical exercises, with answers provided by the author in an extensive solutions manual.
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Book Title: Elements of Nonlinear Time Series Analysis and Forecasting
Number of Pages: Xxi, 618 Pages
Publication Name: Elements of Nonlinear Time Series Analysis and Forecasting
Language: English
Publisher: Springer International Publishing A&G
Publication Year: 2017
Subject: Biostatistics, Probability & Statistics / General, Probability & Statistics / Time Series, Statistics
Type: Textbook
Item Weight: 469.7 Oz
Author: Jan G. De Gooijer
Subject Area: Mathematics, Business & Economics, Medical
Item Length: 10 in
Series: Springer Series in Statistics Ser.
Item Width: 7 in
Format: Hardcover
