Applied Data Mining for Forecasting Using SAS

Chapter 9: Model Building: ARIMAX or Dynamic Regression Modes

Introduction

9.1 ARIMAX Concepts

9.2 ARIMAX Applications

Appendix: Prewhitening and Other Topics Associated with Interval-Valued Input Variables

Introduction

This chapter presents the rational polynomial transfer function framework. It begins with the ordinary regression model in a time series setting. Extensions to the regression framework illustrate how dynamic relationships between inputs and the target can be accommodated using the rational polynomial transfer function. Dynamic relationships include lags, shifts, and persistence effects. Determining the relationships between a model's inputs and the target is called the model identification process. Another topic is accommodating ...