“Backwards” stepwise regression begins with the model including all of the potential independent variables, and successively throws out those which cost the least in terms of reduction of the ...

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 conventional entry test for a new variable in stepwise regression is not theoretically correct, but is used because the necessary exact distributions are not known. Some distributional results ...