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Field name	Details
Dewey Class	519.2
Title	Nonlinear Time Series ([EBook] :) : Nonparametric and Parametric Methods / / by Jianqing Fan, Qiwei Yao.
Author	Fan, Jianqing
Added Personal Name	Yao, Qiwei author.
Other name(s)	SpringerLink (Online service)
Publication	New York, NY : : Springer New York, , 2003.
Physical Details	XX, 552 p. : online resource.
Series	Springer Series in Statistics 0172-7397
ISBN	9780387693958
Summary Note	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.:
Contents note	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.
System details note	Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site	http://dx.doi.org/10.1007/978-0-387-69395-8
Links to Related Works	Subject References: Econometrics . Economics, Mathematical . Mathematics . Probabilities . Probability theory and stochastic processes . Quantitative Finance . Statistical Theory and Methods . Statistics . Authors: Fan, Jianqing . Yao, Qiwei . Corporate Authors: SpringerLink (Online service) . Series: Springer Series in Statistics . Classification: 519.2 .

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Nonlinear Time Series: Nonparametric and Parametric Methods /

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