New technique to estimate the asymmetric trimming mean

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. copyright © 2010 a. m. h. alkhazaleh and a. m. razali.