Question

Describe each step;

1) forward stepwise regression

2) forward selection

3) backward elimination

Answer 1

(1) Stepwise regression is a method of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure. In each step, a variable is considered for addition to or subtraction from the set of explanatory variables based on some prespecified criterion.

(2) Forward selection is a type of stepwise regression which begins with an empty model and adds in variables one by one. In each forward step, you add the one variable that gives the single best improvement to your model.

(3) Backward elimination begins with all variables selected and eliminates variables one at a time until a stopping criterion is reached.