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                                       Details for article 3 of 22 found articles
 
 
  A smooth adaptive estimator of the mean of a symmetric or asymmetric distribution
 
 
Title: A smooth adaptive estimator of the mean of a symmetric or asymmetric distribution
Author: Han, Chien-Pai
Hawkins, D. L.
Appeared in: Communications in statistics
Paging: Volume 23 (1994) nr. 1 pages 1-10
Year: 1994
Contents: We study an adaptive estimate (SA) of the mean of a continuous distribution F based on a quasi-linear combination of order statistics with weights which smoothly adapt to the extremeness of the tail order statistics. SA is based in part on the selector statistic (HG2) of Hogg and Lenth (1984), which has been used widely for estimating the location when F is symmetric. We compare SA to HG2 via Monte Carlo for both symmetric and asymmetric F. We find that SA dominates or ties HG2 for symmetric F with t5 or lighter tails, and enjoys robustness to asymmetric F (not possessed by HG2), for which it competes well with the sample mean.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 3 of 22 found articles
 
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