Modified Regression-Cum-Ratio Types Estimators of Population Coefficient of Variation in Survey Sampling

Abstract

Enhancing the efficiency of estimators is one of the major concerns in sampling survey. Efficiency of estimators measures the precision of  the estimator with respect to the corresponding parameters. In this paper, four methods of estimating the population coefficient of  variation of the study variable using auxiliary information were suggested by modifying some existing estimators using unknown weight and power transformation techniques. The properties (Biases and MSEs) of the proposed estimators were derived up to first order of  approximation using Taylor series approach. Numerical analysis of MSEs and PREs of the proposed and other related existing estimators  considered in the study was conducted to justify the efficiencies of the proposed estimators and the results obtained revealed that the proposed estimators have minimum MSEs and higher PREs compared to competing estimators implying that the proposed estimators  are more efficient than the existing estimators considered in the study.