Fr. 256.00

Nonlinear Time Series - Semiparametric and Nonparametric Methods

English · Hardback

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Zusatztext "?The author has presented the material very carefully ?There are plenty of real examples and all the methods are illustrated. ? I believe the book is extremely useful and definitely will be helpful to many advanced research workers."-Journal of Time Series Analysis! 2009"The monograph provides a timely addition to the subject of nonlinear time series ? the author presents a thorough and rigorous theoretical framework for semiparametric nonlinear time series and analysis."-Scott H. Holan! University of Missouri-Columbia! Journal of the American Statistical Association! June 2009! Vol. 104! No. 486 Informationen zum Autor Gao, Jiti Klappentext Nonlinear Time Series: Semiparametric and Nonparametric Methods focuses on various semiparametric methods in model estimation, specification testing, and selection of time series data. After a brief introduction, the book examines semiparametric estimation and specification methods and then applies these approaches to a class of nonlinear continuous-time models with real-world data. It also assesses some newly proposed semiparametric estimation procedures for time series data with long-range dependence. Even though the book only deals with climatological and financial data, the estimation and specifications methods discussed can be applied to models with real-world data in many disciplines. Zusammenfassung Focuses on the various semiparametric methods in model estimation, specification testing, and selection of time series data. This book examines semiparametric estimation and specification methods and then applies these approaches to a class of nonlinear continuous-time models with real-world data. Inhaltsverzeichnis Introduction. Estimation in Nonlinear Time Series. Nonlinear Time Series Specification. Model Selection in Nonlinear Time Series. Continuous-Time Diffusion Models. Long-Range Dependent Time Series. Appendix. References. Indices.

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