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Estimation of Bowley's Coefficient of Skewness in the Presence of Auxiliary Information

Author

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  • Housila P. Singh
  • Ramkrishna S. Solanki
  • Sarjinder Singh

Abstract

In this paper, we suggest regression-type estimators for estimating the Bowley's coefficient of skewness using auxiliary information. To the first degree of approximation, the bias and mean-squared error expressions of the regression-type estimators are obtained, and the regions under which these estimators are more efficient than the conventional estimator are also determined. Further, a general class of estimators of the Bowley's coefficient of skewness is defined along with its properties. A class of estimators based on estimated optimum values is also defined. It is shown to the first degree of approximations that the variance of the class of estimators based on estimated optimum values is the same as that of the minimum variance of the proposed class of estimators. A simulation study is carried out to demonstrate the performance of the proposed difference estimator over the usual estimator.

Suggested Citation

  • Housila P. Singh & Ramkrishna S. Solanki & Sarjinder Singh, 2014. "Estimation of Bowley's Coefficient of Skewness in the Presence of Auxiliary Information," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(22), pages 4867-4880, November.
  • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:22:p:4867-4880
    DOI: 10.1080/03610926.2012.729644
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