Abstract
This paper presents a new measure of outlier resistance based on Huber's maximum bias. After standardizing by the maximum bias of the median for the same situation, outlier resistance seems to be essentially independent of n and depends on the fraction of contamination. The advantages over alternative measures of resistance involve this relative stability with the sample size, and the ability to measure resistance to a large fraction of outliers. As an example, this method of measuring outlier resistance is applied to a comparison of a 20% trimmed mean with a Huber M-estimator.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 175-181 |
| Number of pages | 7 |
| Journal | Biometrika |
| Volume | 73 |
| Issue number | 1 |
| DOIs | |
| State | Published - Apr 1986 |
Keywords
- Influence curve
- M-estimate
- Maximum bias
- Robustness
- Trimmed mean
ASJC Scopus subject areas
- Statistics, Probability and Uncertainty
- Applied Mathematics
- Mathematics(all)
- Statistics and Probability
- Agricultural and Biological Sciences (miscellaneous)
- Agricultural and Biological Sciences(all)
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Cite this
Rocke, D. M. (1986). Outlier resistance in small samples. Biometrika, 73(1), 175-181. https://doi.org/10.1093/biomet/73.1.175