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Original Articles

Detecting outliers: power and some other considerations

Pages 2299-2314 | Published online: 27 Jun 2007
 

Abstract

The general problem of outlier detection and five recursive outlier detection procedures considered in the study are defined. The methods to compute powers, probabilities of detecting ≥1 outliers, and >1 observations including at least one inlier as outliers are computed and results are discussed. Results show that no procedure is most powerful when the actual number of outlier present in the sample is exactly, under-, and overestimated. The probabilities of inliers being detected as outliers are also substantial particularly when outliers occur only on one side of the sample

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