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Some Modified Linear Regression Type Ratio Estimators for Estimation of Population Mean Using Known Parameters of an Auxiliary Variable

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  • J Subramani
  • G Kumarapandiyan
  • S Balamurali

Abstract

The present paper deals with modified linear regression type ratio estimators for estimation of population mean of the study variable when the Kurtosis, Skewness, population correlation coefficient and quartiles of the auxiliary variable are known. The bias and the mean squared error of the proposed estimators are derived and are compared with that of simple random sampling without replacement (SRSWOR) sample mean, the usual ratio estimator and the existing modified linear regression type ratio estimators. As a result, we have derived the conditions for which the proposed estimators perform better than the other existing estimators. Further the performance of the proposed estimators with that of the existing estimators are assessed for a natural population. From the numerical study it is observed that the proposed modified ratio estimators perform better than the existing estimators.

Suggested Citation

  • J Subramani & G Kumarapandiyan & S Balamurali, 2014. "Some Modified Linear Regression Type Ratio Estimators for Estimation of Population Mean Using Known Parameters of an Auxiliary Variable," Journal of Building Construction, Planning and Materials Research, Conscientia Beam, vol. 1(1), pages 28-42.
    • Handle: RePEc:pkp:jbcpmr:v:1:y:2014:i:1:p:28-42:id:2397
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