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Comparative Study of Synthetic Estimators with Ratio Synthetic Estimator for Domain Mean in Survey Sampling Using Auxiliary Character
Abstract
Domain estimation is an emerging area of research, due to its increasing demand for drafting policy in government as well as in private sectors. Indirect estimator has been widely used in domain estimation because sufficient sampling units are not available. In this paper, we have proposed a class of synthetic estimator for domain mean using auxiliary character and studied its properties. A proposed class of estimators for domain mean using auxiliary character is compared with ratio synthetic estimator for domain mean using auxiliary character theoretically and empirically. The proposed class of estimators for domain mean is found to be more efficient for domain mean using auxiliary character than the ratio synthetic estimator for domain mean using auxiliary character.
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