A Guided Tour of Modern Regression Methods

Abstract

The statistical practitioner today, who wants to find new methods to fit historical data is confronted by a often bewildering morass of acronyms. We will attempt, via a few examples, to shed some light on how techniques such as CART, MARS, GAM, PLS, PCR and ANN work and how they can be used effectively. This paper is based on an invited tutorial on modern regression methods given at the 1995 Fall Technical Conference in St. Louis. KEYWORDS: nonparametric regression; function approximation; neural networks; generalized additive models; tree based regression. 1 Introduction Our aim in this paper is to provide an introduction to several of the more popular regression based techniques currently used by data analysts. Our intent is to familiarize the reader with each technique, not to provide an in-depth analysis of each. We will illustrate the techniques via examples, referring the reader to the vast bibliography on the subject for more details on the estimation and inference properties of..