A Course in Time Series Analysis
Copyright © 2001 John Wiley & Sons, Inc. All rights reserved.
Editor(s): Daniel Peña, George C. Tiao, Ruey S. Tsay
Published Online: 25 JAN 2011 03:25PM EST
Print ISBN: 9780471361640
Online ISBN: 9781118032978
Book Series: Wiley Series in Probability and Statistics
About this Book
New statistical methods and future directions of research in time series
A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include:
- Contributions from eleven of the worldâ??s leading figures in time series
- Shared balance between theory and application
- Exercise series sets
- Many real data examples
- Consistent style and clear, common notation in all contributions
- 60 helpful graphs and tables
Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.