Journal of Modern Mathematics and Statistics

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A Class of Modified Calibration Ratio Estimators of Population Mean with Known Coefficient of Kurtosis in Stratified Double Sampling

Elisha J. Inyang and Etebong P. Clement
Page: 55-60 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

This study proposes a class of ratio estimators of mean for calibration estimation that is more precise and efficient than the linear regression estimator under the stratified double sampling using coefficient of kurtosis of auxiliary variable. Some well-known estimators are obtained under certain prescribed conditions and shown to be special members of this class of estimators. Analytical and numerical results proved the efficacy of the new class of estimators over all existing modified estimators in stratified double sampling with appreciable gains in efficiency at its optimum condition.

How to cite this article:

Elisha J. Inyang and Etebong P. Clement. A Class of Modified Calibration Ratio Estimators of Population Mean with Known Coefficient of Kurtosis in Stratified Double Sampling.
DOI: https://doi.org/10.36478/jmmstat.2020.55.60
URL: https://www.makhillpublications.co/view-article/1994-5388/jmmstat.2020.55.60