In this paper an improved version of Singh's ratio-cum-product estimators is suggested in simple random sampling when two auxiliary variables are available. Using Taylor linearization method we obtain, to the first and second order of approximation, the expressions for the mean square error of the proposed estimators and we establish that they are more efficient than the original ratio-cum-product estimators. Moreover, in order to better evaluate the performance of the estimators, an application to real data is shown.
Improved ratio-cum-product type estimators
PERRI, PIER FRANCESCO
2007-01-01
Abstract
In this paper an improved version of Singh's ratio-cum-product estimators is suggested in simple random sampling when two auxiliary variables are available. Using Taylor linearization method we obtain, to the first and second order of approximation, the expressions for the mean square error of the proposed estimators and we establish that they are more efficient than the original ratio-cum-product estimators. Moreover, in order to better evaluate the performance of the estimators, an application to real data is shown.File in questo prodotto:
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