Forecasting with Univariate Box - Jenkins Models

Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using real data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another. BASIC CONCEPTS.

Overview.

Introduction to Box-Jenkins Analysis of a Single Data Series.

Underlying Statistical Principles.

An Introduction to the Practice of ARIMA Modeling.

Notation and the Interpretation of ARIMA Models.

Identification: Stationary Models.

Identification: Nonstationary Models.

Estimation.

Diagnostic Checking.

Forecasting.

Seasonal and Other Periodic Models.

THE ART OF ARIMA MODELING.

Practical Rules.

References.

Index.

Alan Pankratz is the author of Forecasting with Univariate Box - Jenkins Models: Concepts and Cases, published by Wiley.