Nonlinear Time Series: Nonparametric and Parametric Methods (Springer Series in Statistics) | 
 enlarge | Authors: Jianqing Fan, Qiwei Yao
Publisher: Springer
Category: Book
List Price: $54.95
Buy New: $38.46
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New (13) Used (3) from $38.46
Rating:  2 reviews
Sales Rank: 632763
Media: Paperback
Pages: 552
Number Of Items: 1
Shipping Weight (lbs): 1.8
Dimensions (in): 9.1 x 6.1 x 1.1
ISBN: 0387261427
Dewey Decimal Number: 332
EAN: 9780387261423
Publication Date: August 4, 2005
Availability: Usually ships in 1-2 business days
Shipping: International shipping available
Condition: THIS IS ITEM IS UNUSED AND IN GOOD CONDITION. IT MAY HAVE SLIGHT SHELFWEAR BUT OTHERWISE IT IS FINE.
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Product Description
This book presents the contemporary statistical methods and theory of nonlinear time series analysis. The principal focus is on nonparametric and semiparametric techniques developed in the last decade. It covers the techniques for modelling in state-space, in frequency-domain as well as in time-domain. To reflect the integration of parametric and nonparametric methods in analyzing time series data, the book also presents an up-to-date exposure of some parametric nonlinear models, including ARCH/GARCH models and threshold models. A compact view on linear ARMA models is also provided. Data arising in real applications are used throughout to show how nonparametric approaches may help to reveal local structure in high-dimensional data. Important technical tools are also introduced. The book will be useful for graduate students, application-oriented time series analysts, and new and experienced researchers. It will have the value both within the statistical community and across a broad spectrum of other fields such as econometrics, empirical finance, population biology and ecology. The prerequisites are basic courses in probability and statistics. Jianqing Fan, coauthor of the highly regarded book Local Polynomial Modeling, is Professor of Statistics at the University of North Carolina at Chapel Hill and the Chinese University of Hong Kong. His published work on nonparametric modeling, nonlinear time series, financial econometrics, analysis of longitudinal data, model selection, wavelets and other aspects of methodological and theoretical statistics has been recognized with the Presidents' Award from the Committee of Presidents of Statistical Societies, the Hettleman Prize for Artistic and Scholarly Achievement from the University of North Carolina, and by his election as a fellow of the American Statistical Association and the Institute of Mathematical Statistics. Qiwei Yao is Professor of Statistics at the London School of Economics and Political Science. He is an elected member of the International Statistical Institute, and has served on the editorial boards for the Journal of the Royal Statistical Society (Series B) and the Australian and New Zealand Journal of Statistics.
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| Customer Reviews:
Well used already! August 30, 2006
Thomas J. Harris (Kingston, ONtario)
3 out of 3 found this review helpful
This is an excellent monograph. The authors have provided an up-to-date analysis of parametric and nonparametric methods with a comprehensive bibliography. The book is very readible. The authors combine elements of descriptive overview, nontrivial examples and theorems / proofs.
A good book March 2, 2008
Xiaorong Yang
1 out of 1 found this review helpful
This book introduces some basal concepts and also includes the recent technology in nonlinear time series. It's not difficult to understand even if you are a novel. The cited references may help you to go further steps in this area.
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