Linear regression taking into account errors in both axes in the presence of outliers

This paper presents guidelines for obtaining the correct regression line by taking into account the errors in both axes when there are outliers in the data set. We have adapted the weighted residual plots to take into account the experimental errors in both axes, and have combined it with robust regression methods and methods for detecting outliers. The protocol has been checked with real data sets from the literature to show how it can be used to find the best regression line when there are outliers in the data set. In all cases the errors in both axes are taken into account.