Journal of Probability and Statistics
Volume 2010 (2010), Article ID 739154, 9 pages
Research Article

New Technique to Estimate the Asymmetric Trimming Mean

Faculty of Science and Technology, National University of Malaysia, 43600 UKM Bangi, Selangor D.E., Malaysia

Received 19 May 2010; Accepted 16 September 2010

Academic Editor: A. Thavaneswaran

Copyright © 2010 A. M. H. Alkhazaleh and A. M. Razali. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A trimming mean eliminates the extreme observations by removing observations from each end of the ordered sample. In this paper, we adopted the Hogg's and Brys's tail weight measures. In addition, a new algorithm was proposed as a linear estimator based on the quartile; we used a quartile to divide the data into three and four groups. Then two new estimators were proposed. These classes of linear estimators were examined via simulation method over a variety of asymmetric distributions. Sample sizes 50, 100, 150, and 200 were generated using R program. The results of 50 were tabulated, since we have similar results for the other sizes. These results were tabulated for 7 asymmetric distributions with total trimmed proportions 0.10 and 0.20 on both sides, respectively. The results for these estimators were ordered based on their relative efficiency.