Improved ratio-type estimators using maximum and minimum values under simple random sampling scheme

Year 2015, Volume: 44 Issue: 4, 923 - 931, 01.08.2015

Mursala Khan Saif Ullah Abdullah Y. Al-hossain Neelam Bashir

Abstract

This paper presents a class of ratio-type estimators for the evaluation
of finite population mean under maximum and minimum values by
using knowledge of the auxiliary variable. The properties of the proposed estimators in terms of biases and mean square errors are derived
up to first order of approximation. Also, the performance of the proposed class of estimators is shown theoretically and these theoretical
conditions are, then, verified numerically by taking three natural populations under which the proposed class of estimators performed better
than other competing estimators. 

Keywords

Study variable, Auxiliary variable, Ratio estimators, Maximum and Minimum values, Simple random sampling, Mean squared error, Efficiency

References

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