ON THE COMBINATION OF ESTIMATORS OF FINITE POPULATION MEAN USING INCOMPLETE MULTIAUXILIARY INFORMATION

  • Neha Garg School of Sciences, Indira Gandhi National Open University, New Delhi, India.
  • Meenakshi Srivastava Department of Statistics, Institute of Social Sciences, Dr. B. R. Ambedkar University, Agra, India
Keywords: Bias, Mean Square Error, Incomplete Multi-Auxiliary Information

Abstract

The present study is concerned with the estimation of a finite population mean when we have information on several auxiliary variables only for some part of the population. The maximum utilization of incomplete multi-auxiliary information is carried out in such cases by stratifying the population on the basis of available multi-auxiliary information at hand. This paper deals with the situation where some of the auxiliary variables are positively and some of them are negatively correlated with the main variable. For this purpose, in this paper ratio-cum-product and regression-cum-product type estimators are considered for estimating the mean of the finite population utilizing available incomplete multi-auxiliary information. The approximate expressions for bias and mean square error of the suggested estimators have also been derived and theoretical results are numerically supported.

 

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Published
2016-12-16
Section
Articles