On improvement in estimating the population mean in simple random sampling

Sat Gupta and Javid Shabbir

Journal of Applied Statistics, 2008, vol. 35, issue 5, 559-566

Abstract: 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.

Keywords: ratio-type estimators; mean square error (MSE); transformation; efficiency (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (8)

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DOI: 10.1080/02664760701835839

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