Nonlinear time series : nonparametric and parametric methods /
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. A distinct feature of this book is that it applies many modern nonparametric estimation and testing ideas to time series mo...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York :
Springer,
[2003]
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| Series: | Springer series in statistics.
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| Subjects: | |
| Online Access: | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=98882 |
| Summary: | 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. A distinct feature of this book is that it applies many modern nonparametric estimation and testing ideas to time series modeling and model identification, while outlines many useful ideas from more traditional time series analysis. This will enable readers to use modern data-analytic techniques while keeping in touch with traditional approaches, and make the book self-contained. 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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| Physical Description: | 1 online resource (551 pages) : illustrations. |
| Bibliography: | Includes bibliographical references and indexes. |
| ISBN: | 9780387224329 0387224327 9780585472560 0585472564 9780387693958 0387693955 |
