Nonlinear Time Series: Nonparametric and Parametric Methods (Springer Series in Statistics)

3,67 valoración promedio
( 6 valoraciones por Goodreads )
 
9780387261423: Nonlinear Time Series: Nonparametric and Parametric Methods (Springer Series in Statistics)
Críticas:

"...the authors should be congratulated for writing a coherent monograph on modern time series analysis with a focus on nonparametric approaches. I believe that this book will become a standard reference in this area and remain so for a long time. Graduate students in statistics, economics, and financial engineering should be happy to have a much-needed textbook on modern time series methods, which covers not only ARIMA models, but also the newer and more flexible nonlinear and nonparametric techniques." Technometrics, February 2004 "This is a book that one can read as a beginner or as an expert. Although there are plenty of theorems, there are also plenty of numerical examples, with both real and simulated data, and lots of pictures and graphics (SPLUS-style). The topics are very fully explained and discussed, and there are many pointers to the literature for further study (with about six hundred references listed)." ISI Short Book Reviews, Vol. 24/1, Apr. 2004 "Fan and Yao's book has a lot to offer. First, it is readable, even by those with limited knowledge of time-series analysis, as the authors spend time on all the basic concepts. Second, it is self-contained so you do not need other books to understand it. Third, it contains many examples and illustrations to explain the intuition behind the concepts. Fourth, it is up to date and has the latest cutting-edge methods to handle nonlinear time series." Quantitative Finance, 2004

Críticas:

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)

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Jianqing Fan, Qiwei Yao
Editorial: Springer-Verlag New York Inc., United States (2005)
ISBN 10: 0387261427 ISBN 13: 9780387261423
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Descripción Springer-Verlag New York Inc., United States, 2005. Paperback. Estado de conservación: New. 1st ed. 2003. 2nd printing 2005. 232 x 154 mm. Language: English . Brand New Book. 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. Nº de ref. de la librería LIB9780387261423

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Jianqing Fan, Qiwei Yao
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Descripción Springer New York 2005-08-04, New York, NY, 2005. paperback. Estado de conservación: New. Nº de ref. de la librería 9780387261423

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Jianqing Fan, Qiwei Yao
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ISBN 10: 0387261427 ISBN 13: 9780387261423
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Descripción Springer-Verlag New York Inc., United States, 2005. Paperback. Estado de conservación: New. 1st ed. 2003. 2nd printing 2005. 232 x 154 mm. Language: English . Brand New Book. 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. Nº de ref. de la librería LIB9780387261423

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Descripción Springer-Verlag New York Inc., 2005. PAP. Estado de conservación: New. New Book. Delivered from our UK warehouse in 3 to 5 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería LQ-9780387261423

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Fan, Jianqing; Yao, Qiwei
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Descripción Springer, 2005. Estado de conservación: New. Nº de ref. de la librería L9780387261423

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Descripción Springer, 2005. Paperback. Estado de conservación: NEW. 9780387261423 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Nº de ref. de la librería HTANDREE0272525

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Descripción Springer Aug 2005, 2005. Taschenbuch. Estado de conservación: Neu. 235x155x30 mm. Neuware - 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. 552 pp. Englisch. Nº de ref. de la librería 9780387261423

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Jianqing Fan, Qiwei Yao
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Descripción Springer, 2005. Paperback. Estado de conservación: New. This item is printed on demand. Nº de ref. de la librería DADAX0387261427

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Descripción Springer Aug 2005, 2005. Taschenbuch. Estado de conservación: Neu. 23.5x15.5x cm. Neuware - 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. 552 pp. Englisch. Nº de ref. de la librería 9780387261423

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