Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1152490 | Statistics & Probability Letters | 2011 | 7 Pages |
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Evrim Oral, Ece Oral,