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http://dx.doi.org/10.5351/KJAS.2018.31.3.397

A bias adjusted ratio-type estimator  

Oh, Jung-Taek (Department of Statistics, Hankuk University of Foreign Studies)
Shin, Key-Il (Department of Statistics, Hankuk University of Foreign Studies)
Publication Information
The Korean Journal of Applied Statistics / v.31, no.3, 2018 , pp. 397-408 More about this Journal
Abstract
Various methods for accurate parameter estimation have been developed in a sample survey and it is also common to use a ratio estimator or the regression estimator using auxiliary information. The ratio-type estimator has been used in many recent studies and is known to improve the accuracy of estimation by adjusting the ratio estimator. However, various studies are under way to solve it since the ratio-type estimator is biased. In this study, we propose a generalized ratio-type estimator with a new parameter added to the ratio-type estimator to remove the bias. We suggested a method to apply this result to the parameter estimation under the error assumption of heteroscedasticity. Through simulation, we confirmed that the suggested generalized ratio-type estimator gives good results compared to conventional ratio-type estimators.
Keywords
bias; unbiased estimator; heteroscedastic; MLE; Taylor approximation;
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Times Cited By KSCI : 2  (Citation Analysis)
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