A Class of Almost Unbiased Estimators for Finite Populations Mean Using Two Auxiliary Variables

Kadilar and Cingi [Ratio estimators in simple random sampling, Appl. Math. Comput. 151 (3) (2004), pp. 893-902] introduced some ratio-type estimators of finite population mean under simple random sampling. Recently, Kadilar and Cingi [New ratio estimators using correlation coefficient, Interstat 4 (2006), pp. 1-11] have suggested another form of ratio-type estimators by modifying the estimator developed by Singh and Tailor [Use of known correlation coefficient in estimating the finite population mean, Stat. Transit. 6 (2003), pp. 655-560]. Kadilar and Cingi [Improvement in estimating the population mean in simple random sampling, Appl. Math. Lett. 19 (1) (2006), pp. 75-79] have suggested yet another class of ratio-type estimators by taking a weighted average of the two known classes of estimators referenced above. In this article, we propose an alternative form of ratio-type estimators which are better than the competing ratio, regression, and other ratio-type estimators considered here. The results are also supported by the analysis of three real data sets that were considered by Kadilar and Cingi.ratio-type estimators, mean square error (MSE), transformation, efficiency,

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A Class of Almost Unbiased Estimators for Finite Populations Mean Using Two Auxiliary Variables

Cited by 10 publications

References 9 publications

An improved estimator of finite population mean when using two auxiliary attributes

An improved estimator of finite population mean when using two auxiliary attributes

On the use of transformed auxiliary variables in estimating population mean by using two auxiliary variables

On improvement in estimating the population mean in simple random sampling

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