Comparative performance of different ratio estimators of population mean
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Date
2018
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CCSHAU
Abstract
In this study, an attempt has been made to compare the performance of
different ratio estimators. For the said purpose, ratio estimators by different
researchers have been taken. Comparison of proposed estimators have been done pair
wise over bias and mean squared error. Theoretical conditions were also developed
when one estimator is better than the other. A total of forty six conditions were found
on each bias and mean square error. Theoretical conditions were also compared using
the empirical data set in which all the parameters required for the estimators were
calculated. R-software code also developed to compare the bias, mean square error
and percentage relative bias for different estimators. It was observed that estimator
proposed by Subramani and Kumarapandiyan ( ere found be the best in term
of bias, mean square and percentage relative bias with all the proposed estimators
whereas estimator proposed by Kadilar and Cingi (2004) found to be the worst
estimator empirically.
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