Algorithm 6.2 Forward stepwise selection
1. Let M0 denote the null model, which contains no predictors.
2. For k = 0, . . . , p − 1:
(a) Consider all p − k models that augment the predictors in Mk
with one additional predictor.
(b) Choose the best among these p − k models, and call it Mk+1.
Here best is defined as having smallest RSS or highest R2.
3. Select a single best model from among M0, . . . ,Mp using crossvalidated
prediction error, Cp (AIC), BIC, or adjusted R2.