Forecasting with Dynamic Regression Models

One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

Auteur
Alan Pankratz is the author of Forecasting with Dynamic Regression Models, published by Wiley.

Contenu
A Primer on ARIMA Models.

A Primer on Regression Models.

Rational Distributed Lag Models.

Building Dynamic Regression Models: Model Identification.

Building Dynamic Regression Models: Model Checking, Reformulation,and Evaluation.

Intervention Analysis.

Intervention and Outlier Detection and Treatment.

Estimation and Forecasting.

Dynamic Regression Models in a Vector ARMA Framework.

Appendices.

References.

Index.