New Technique to Estimate the Asymmetric Trimming Mean

• Main Authors: A. M. H. Alkhazaleh, A. M. Razali
• Format: Article
• Language: English
• Published: Hindawi Limited 2010-01-01
• Series: Journal of Probability and Statistics
• Online Access: http://dx.doi.org/10.1155/2010/739154

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.