Fan Jianqing, Yao Qiwei Nonlinear Time Series / Nonparametric and Parametric Methods 9780387261423

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Автор: Fan Jianqing, Yao Qiwei
Название: Nonlinear Time Series / Nonparametric and Parametric Methods
Перевод названия: Нелинейный временной ряд / непараметрические и параметрические методы
ISBN: 9780387261423
Издательство: Springer
Классификация:

Эконометрика

Вероятность и статистика

Прикладная математика

ISBN-10: 0387261427
Обложка/Формат: Paperback
Страницы: 571
Вес: 0.80 кг.
Дата издания: 07.09.2005
Серия: Springer Series in Statistics
Язык: English
Издание: 1st ed. 2003. 2nd pr
Иллюстрации: Illustrations
Размер: 23.39 x 15.60 x 2.97
Читательская аудитория: Postgraduate, research & scholarly
Подзаголовок: Nonparametric and parametric methods
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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.
Дополнительное описание: Формат: 235x155
Круг читателей: Researchers, graduate students
Ключевые слова:
Язык: eng
Издание: 1st ed. 2003. 2nd printin
Оглавление: Introduction.- 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.

Nonlinear Time Series / Nonparametric and Parametric Methods, Fan Jianqing, Yao Qiwei