Here, at each step, a single predictor is eliminated from the current regression model if its removal would increase the sum-of-squares differences between the observed and the predicted values, by not more than F out (some properly chosen constant, typically between 2 and 4) times the residual mean square RSS n−p , where n is the number of observations and p is the number of predictors.
the predictor giving the smallest increase in RSS is chosen.