We introduce a fast stepwise regression method, called the orthogonal greedy algorithm (OGA), that selects input variables to enter a p-dimensional linear regression model (with p ≫ n, the sample size ...

The first step in conducting a regression-based study is to specify a model. In real applications, this is usually the most challenging step - deciding which variables “belong” in the model and which ...

This is an expository paper, pointing out explicitly the pseudoness of the "F-statistic" used in stepwise procedures for determining the independent variables to be used in a linear prediction ...