Some improved estimators for estimating population mean in stratified random sampling

TL;DR

This paper introduces improved estimators for population mean in stratified sampling using auxiliary info, demonstrating their superiority over traditional methods through theoretical and empirical analysis.

Contribution

The paper proposes new estimators with lower mean square error for stratified sampling, enhancing accuracy over existing estimators.

Findings

Proposed estimators have lower MSE than traditional estimators.

Theoretical derivations confirm improved efficiency under optimal conditions.

Empirical results support the effectiveness of the new estimators.

Abstract

Some improved estimators are proposed for estimating the population mean in stratified sampling in the presence of auxiliary information. Mean square error (MSE) of the proposed estimators have been derived under large sample approximation. It has been shown that under optimum conditions proposed estimators are better than usual unbiased estimator and Hansen (1946) estimator. Both theoretical and empirical findings are encouraging and support the soundness of the proposed procedure for mean estimation.