A Course in Time Series Analysis

A Course in Time Series Analysis

Editor(s): Daniel Peña, George C. Tiao, Ruey S. Tsay

Published Online: 25 JAN 2011 03:25PM EST

Print ISBN: 9780471361640

Online ISBN: 9781118032978

DOI: 10.1002/9781118032978

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.

Table of contents

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  1. Part I: Basic Concepts in Univariate Time Series

  2. Part II: Advanced Topics in Univariate Time Series

  3. Part III: Multivariate Time Series

    1. You have free access to this content
    1. You have free access to this content