A Robust Subset Selection Procedure for Location Parameter Based on Hodges-Lehmann Estimators

This paper deals with a robust subset selection procedure based on Hodges-Lehmann estimators of location parameters. An improved formula for the estimated standard error of Hodges-Lehmann estimators is considered. Also, the degrees of freedom of the studentized Hodges-Lehmann estimators are investigated and it is suggested to use 0.8n instead of n-1. The proposed procedure is compared with the other subset selection procedures and it is shown to have good effciency for heavy-tailed distributions.