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-doma
Nonlinear Time Series Nonparametric and Parametric Methods
✍ Scribed by Jianqing Fan, Qiwei Yao
- Publisher
- Springer
- Year
- 2003
- Tongue
- English
- Leaves
- 569
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
✦ Subjects
Финансово-экономические дисциплины;Анализ и прогнозирование временных рядов;
📜 SIMILAR VOLUMES
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 dimensio
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 dimensio
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 dimensio
Methods of nonlinear time series analysis are discussed from a dynamical systems perspective on the one hand, and from a statistical perspective on the other. After giving an informal overview of the theory of dynamical systems relevant to the analysis of deterministic time series, time series gener