Abstract
We examine the efficiency of the mean deviation and Gini's mean difference (the mean of all pairwise distances). Our findings support the viewpoint that Gini's mean difference combines the advantages of the mean deviation and the standard deviation.
Original language | English |
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Pages (from-to) | 569-596 |
Number of pages | 28 |
Journal | Statistical Methods & Applications |
Volume | 24 |
Issue number | 4 |
Early online date | 7 May 2015 |
DOIs | |
Publication status | Published - Nov 2015 |
Bibliographical note
18 pages, 3 figures, 8 tablesAcknowledgments
We are indebted to Herold Dehling for introducing us to the theory of U-statistics, to Roland Fried for introducing us to robust statistics, and to Alexander Dürre, who has demonstrated the benefit of complex analysis for solving statistical problems. Both authors were supported in part by the Collaborative Research Centre 823 Statistical modelling of nonlinear dynamic processes.
Keywords
- math.ST
- stat.TH
- 62G35, 62G05, 62G20
- influence function
- mean deviation
- median absolute deviation
- normal mixture distribution
- residue theorem
- robustness