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  • 标题:New Efficient Estimators of Population Mean Using Non-Traditional Measures of Dispersion
  • 本地全文:下载
  • 作者:Rajesh Kumar Gupta ; Subhash Kumar Yadav
  • 期刊名称:Open Journal of Statistics
  • 印刷版ISSN:2161-718X
  • 电子版ISSN:2161-7198
  • 出版年度:2017
  • 卷号:07
  • 期号:03
  • 页码:394-404
  • DOI:10.4236/ojs.2017.73028
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:One of the aims in survey sampling is to search for the estimators with highest efficiency. In the present paper, three improved estimators of population mean have been proposed using some non-traditional measures of dispersion of auxiliary variable such as Gini’s mean difference, Downton’s method and probability weighted moments early given by Abid [1] with a special population parameter of auxiliary variable. The large sample properties that are biased and mean squared errors of the proposed estimators have been derived up to the first order of approximation. A theoretical comparison of the proposed estimators has been made with the other existing estimators of population mean using auxiliary information. The conditions under which the proposed estimators perform better than the other existing estimators of population mean have been given. A numerical study is also carried out to see the performances of the proposed and existing estimators of population mean and verify the conditions under which proposed estimators are better than other estimators. It has been shown that the proposed estimators perform better than the existing estimators as they are having lesser mean squared error.
  • 关键词:Study Variable;Auxiliary Variable;Bias;Mean Squared Error;Efficiency
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