Comment.

The article presents comments on an article published in the March 01, 2002 issue of the periodical "Journal of the American Statistical Association." Data acquisition is much less expensive today than, say 20 years ago. Therefore, modern statistical methods should be able to cope with large datasets. This is particularly true for linear regression methods, because they are widely used in many applications. Positive-breakdown estimators have been developed to protect against outlying data points, but they are often hard to compute exactly. Although, authors proposing a new algorithm usually focus on its computation time and performance, Hawkins and Olive in the first part of their article take a closer look at the breakdown value and the (in)consistency of algorithm based on elemental samples. Contrary to Hawkins and Olive, the authors find the extreme computational load of the X-cluster algorithm problematic. In their experience, practitioners can rarely he convinced to use a method that cannot be computed within reasonable time.