A robust alternative to the ratio estimator under non-normality |
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Authors: | Evrim Oral Ece Oral |
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Institution: | a Louisiana State University HSC, School of Public Health, Biostatistics Program, New Orleans, LA 70112, USAb The Central Bank of the Republic of Turkey, Research and Monetary Department, Ankara 06100, Turkey |
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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. |
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Keywords: | Ratio-type estimators Simple random sampling Order statistics Non-normality Robustness |
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