Электронный каталог

31
F 23 us
Fan, Jianqing.
    Nonlinear time series: Nonparametric and Parametric Methods [Электронный ресурс] / Jianqing Fan, Qiwei Yao. - New York : Springer, 2003. - 571 p. - ISBN 0-387-95170-9 : Б. ц.

УДК

31

Кл.слова (ненормированные):
Statistical methods -- Theory of nonlinear time series
Аннотация: 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.
Доп.точки доступа:
Yao, Qiwei

Свободных экз. нет

31
G 17 us
Gao, Jiti.
    Nonlinear time series, semiparametric and nonparametric methods [Электронный ресурс] / Jiti Gao. - [S. l.] : Chapman & Hall/CRC, 2007. - 237 p. - (Monographs on Statistics and Applied Probability). - Б. ц.

УДК

31

Кл.слова (ненормированные):
Statistical methods -- Theory of nonlinear time series
Аннотация: Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fully nonparametric models and methods. Answering the call for an up-to-date overview of the latest developments in the field, "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, 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. It also assesses some newly proposed semiparametric estimation procedures for time series data with long-range dependence. Even though this 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. This resource covers key methods in time series analysis and provides the necessary theoretical details. The latest applied finance and financial econometrics results and applications presented in this book enable researchers and graduate students to keep abreast of developments in the field.
Свободных экз. нет