Jianqing Fan, Qiwei Yao

Nonlinear Time Series (eBook, PDF)

Nonparametric and Parametric Methods

• Format: PDF

Produktbeschreibung

This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.

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Produktdetails

• Verlag: Springer New York
• Seitenzahl: 552
• Erscheinungstermin: 11. September 2008
• Englisch
• ISBN-13: 9780387693958
• Artikelnr.: 43999851

Autorenporträt

Jianqing Fan, Princeton University, Princeton, NJ, USA / Qiwei Yao, London School of Economics, London, UK

Inhaltsangabe

Characteristics of Time Series.- ARMA Modeling and Forecasting.- Parametric Nonlinear Time Series Models.- Nonparametric Density Estimation.- Smoothing in Time Series.- Spectral Density Estimation and Its Applications.- Nonparametric Models.- Model Validation.- Nonlinear Prediction.

Rezensionen

From the reviews:

"The book will particularly appeal to those in the economic sciences and financial engineering who have a solid background in linear time series models and methods. ... I would recommend it to postgraduate students who are interested in learning about recent developments in non-linear and non-parametric time series modelling as well as in understanding the use of complex parametric non-linear and non-parametric time series models in practice." (Jiti Gao, Australian Journal of Agricultural and Resource Economics, Vol. 49, 2005)