How Does Stepwiselm Work?

The stepwiselm function uses forward and backward stepwise regression to determine a final model. At each step, the function searches for terms to add to the model or remove from the model based on the value of the 'Criterion' name-value pair argument.

How does stepwise selection work?

As the name stepwise regression suggests, this procedure selects variables in a step-by-step manner. The procedure adds or removes independent variables one at a time using the variable's statistical significance. Stepwise either adds the most significant variable or removes the least significant variable.

What is forward selection method?

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.