An Efficient Exponential Ratio and Product Type Estimator in Post-Stratification

Rubal Sharma, Sangeeta Malik

Abstract: In this paper we present a unique estimator for the population parameter under post-stratification. By segmenting the population into homogeneous subgroups, post-stratification is a widely used strategy in survey sampling that increases the accuracy of estimators. In the post-stratification scenario, this paper addressed the issue of estimating the mean of a finite population. For post-stratification, better separate ratio and product exponential type estimators are proposed. This studys primary goal is to evaluate our suggested estimators performance against that of current estimators. We perform a thorough simulation research to assess the precision and effectiveness of our estimator. The mean squared errors and biases of the proposed estimators are obtained to the first degree of approximation. Theoretical and practical researches have demonstrated that the proposed estimators are more efficient than other estimators that were taken into consideration.

Keywords: Finite populations mean, post-stratification, bias, mean square error, percent relative efficiency