Improved Exponential Type Estimators of Finite Population Mean under Complete and Partial Auxiliary Information

This paper proposes some improved exponential type estimators of finite population mean under simple random sampling and double sampling. Expressions for biases and mean squared errors of the proposed estimators are derived up to the first order of approximation. Theoretical and numerical comparisons are made to investigate the performances of the estimators. The proposed estimators always perform better than the difference estimator of the population mean. They also perform better than the estimators suggested by Gupta and Shabbir [3] and Grover and Kaur [2].