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.