where y is the sample mean of the study variable, y, and b is a suitable constant, often chosen to be close to
the population regression coefficient of y on x. In the present study, we introduce a class of estimators, which is
both a generalization and an extension of the estimators (3) to (8), proposed by [1]. We observe that apart from
the customary ratio estimator, ˆR= y x , other estimators of the population ratio, R, in literature, like those
proposed by [7]-[9], often require additional information on some auxiliary variables, and consequently involving
extra funds. Reference [1] argued that such extra costs could be avoided by using variable transformation of
the already observed auxiliary variable, x. Accordingly, cost reduction in constructing estimators of the population
ratio, R, is a strong motivation for the general class of estimators, which the present study seeks to introduce
in the estimation of population ratio, R, using variable transformation.
where y is the sample mean of the study variable, y, and b is a suitable constant, often chosen to be close to
the population regression coefficient of y on x. In the present study, we introduce a class of estimators, which is
both a generalization and an extension of the estimators (3) to (8), proposed by [1]. We observe that apart from
the customary ratio estimator, ˆR= y x , other estimators of the population ratio, R, in literature, like those
proposed by [7]-[9], often require additional information on some auxiliary variables, and consequently involving
extra funds. Reference [1] argued that such extra costs could be avoided by using variable transformation of
the already observed auxiliary variable, x. Accordingly, cost reduction in constructing estimators of the population
ratio, R, is a strong motivation for the general class of estimators, which the present study seeks to introduce
in the estimation of population ratio, R, using variable transformation.
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