ABSTRACT

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

chapter 1|14 pages

Introduction

chapter 2|34 pages

Estimation in Nonlinear Time Series

chapter 3|34 pages

Nonlinear Time Series Specification

chapter 4|28 pages

Model Selection in Nonlinear Time Series

chapter 5|46 pages

Continuous–Time Diffusion Models

chapter 6|36 pages

Long–Range Dependent Time Series

chapter 7|16 pages

Appendix