A resistant test for simple linear regression

A new nonparametric test for simple linear regression that is resistant to gross errors is introduced for resting the null hypothesis H-0:alpha = alph a(0), beta = beta(0) against all alternatives. Using test resistances, the proposed lest is shown to be more resistant to gross errors than the Brown- Mood and the Lancaster-Quade tests. Next, an alternative point extimate for the slope is proposed. It is shown that the proposed estimator attains the highest possible breakdown point. Finally, these findings are illustrated by an example.