Key points are not available for this paper at this time.
This article is concerned with “many outlier” procedures i.e., procedures that can detect more than one outlier in a sample. Several many outlier procedtues are proposed in Section 2 and via power comparisons in Section 3 are found to be much superior to one outlier procedures in detecting many outliers. We then compare several different. many outlier procedures in Section 4 and find that the procedutre based on the extreme studentized deviate (ESD) is slightly the best. Finally, 5%, 1% and .5% points are given for the ESD procedure for various sample sizes in Section 5.
Bernard Rosner (Thu,) studied this question.