An Optimum Allocation with a Family of Estimators Using Auxiliary Information in Sample Survey

Abstract

The problem of obtaining optimum allocation using auxiliary information in stratified random sampling. An optimum allocation with a family of estimators is obtained and its efficiency is compared with that of Neyman allocation based on Srivastava (1971) class of estimators and the optimum allocation suggested by Zaidi et al., (1989). It is shown that the proposed allocation is better in the sense having smaller variance compared to other optimum allocation.