A robust alternative to the ratio estimator under non-normality

Evrim Oral and Ece Oral ()

Statistics & Probability Letters, 2011, vol. 81, issue 8, 930-936

Abstract: In sampling theory, the traditional ratio estimator is the most common estimator of the population mean when the correlation between study and auxiliary variables is positively high. We introduce a new ratio-type estimator based on the order statistics of a simple random sample. We show that this new estimator is considerably more efficient than the traditional ratio estimator under non-normality, and remarkably robust to data anomalies such as presence of outliers in data sets.

Keywords: Ratio-type; estimators; Simple; random; sampling; Order; statistics; Non-normality; Robustness (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (1)

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