Nonlinear Time Series
Nonparametric and Parametric Methods
Authors: Fan, Jianqing, Yao, Qiwei
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- About this book
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Amongmanyexcitingdevelopmentsinstatisticsoverthelasttwodecades, nonlineartimeseriesanddata-analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths. In spite of the fact that the - plication of nonparametric techniques in time series can be traced back to the 1940s at least, there still exists healthy and justi?ed skepticism about the capability of nonparametric methods in time series analysis. As - thusiastic explorers of the modern nonparametric toolkit, we feel obliged to assemble together in one place the newly developed relevant techniques. Theaimofthisbookistoadvocatethosemodernnonparametrictechniques that have proven useful for analyzing real time series data, and to provoke further research in both methodology and theory for nonparametric time series analysis. Modern computers and the information age bring us opportunities with challenges. Technological inventions have led to the explosion in data c- lection (e.g., daily grocery sales, stock market trading, microarray data). The Internet makes big data warehouses readily accessible. Although cl- sic parametric models, which postulate global structures for underlying systems, are still very useful, large data sets prompt the search for more re?nedstructures,whichleadstobetterunderstandingandapproximations of the real world. Beyond postulated parametric models, there are in?nite other possibilities. Nonparametric techniques provide useful exploratory tools for this venture, including the suggestion of new parametric models and the validation of existing ones.
- Reviews
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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)
- Table of contents (10 chapters)
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Introduction
Pages 1-27
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Characteristics of Time Series
Pages 29-88
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ARMA Modeling and Forecasting
Pages 89-123
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Parametric Nonlinear Time Series Models
Pages 125-192
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Nonparametric Density Estimation
Pages 193-214
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Table of contents (10 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Nonlinear Time Series
- Book Subtitle
- Nonparametric and Parametric Methods
- Authors
-
- Jianqing Fan
- Qiwei Yao
- Series Title
- Springer Series in Statistics
- Copyright
- 2003
- Publisher
- Springer-Verlag New York
- Copyright Holder
- Springer-Verlag New York
- eBook ISBN
- 978-0-387-69395-8
- DOI
- 10.1007/978-0-387-69395-8
- Softcover ISBN
- 978-0-387-26142-3
- Series ISSN
- 0172-7397
- Edition Number
- 1
- Number of Pages
- XX, 552
- Topics
