ESTIMATION OF POPULATION MEAN THROUGH IMPROVED CLASS OF RATIO TYPE ESTIMATORS USING AUXILIARY INFORMATION

  • Banti Kumar Division of Statistics and Computer Science, FBSc, Sher-e- Kashmir University of Agricultural Sciences and Technology of Jammu, India
  • Manish Kumar Division of Statistics and Computer Science, FBSc, Sher-e- Kashmir University of Agricultural Sciences and Technology of Jammu, India
  • S.E.H. Rizvi Division of Statistics and Computer Science, FBSc, Sher-e- Kashmir University of Agricultural Sciences and Technology of Jammu, India
  • M. Iqbal Jeelani Bhat Division of Statistics and Computer Science, FBSc, Sher-e- Kashmir University of Agricultural Sciences and Technology of Jammu, India
Keywords: Auxiliary Information, Ratio Estimator, Relative Bias, Relative Mean Squared Error, Population Mean

Abstract

In survey sampling we are often concerned with the estimation of population parameters with the use of auxiliary information at pre-selection stage, selection stage and estimation stage. If used properly, this information may provide better estimates than those where such information is not used. In this paper, an attempt has been made to develop a general class of improved ratio type estimators for estimation of population mean by modifying conventional ratio estimator whose large sample properties are compared with the conventional ratio estimator and estimators proposed by Sharma et al. (2010). It is observed that the proposed class of estimators performed better than conventional ratio estimator and estimators proposed by Sharma et al. (2010) on the basis of unbiasedness, mean squared error and efficiency criterion. An empirical study has also been presented in support of the present investigation.

 

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Published
2018-03-05
Section
Articles