附註:Includes bibliographical references and indexes.
1. Introduction -- 2. Characteristics of Time Series -- 3. ARMA Modeling and Forecasting -- 4. Parametric Nonlinear Time Series Models -- 5. Nonparametric Density Estimation -- 6. Smoothing in Time Series -- 7. Spectral Density Estimation and Its Applications -- 8. Nonparametric Models -- 9. Model Validation -- 10. Nonlinear Prediction.
摘要: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. A distinct feature of this book is that it applies many modern nonparametric estimation and testing ideas to time series modeling and model identification, while outlines many useful ideas from more traditional time series analysis. This will enable readers to use modern data-analytic techniques while keeping in touch with traditional approaches, and make the book self-contained. 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.
