High-Breakdown Estimators is a class of robust statistical estimation methods that belong to the broader category of location and scale estimators, distinguished by their ability to withstand contamination from a large proportion of outliers, typically possessing a breakdown point approaching 50%.
115
Publications
9.7K
Citations
134
Authors
101
Institutions
Publications per year
2017–2026
4
Parents
Publications
115
1–5 of 115
Authors
134
- PJ
10
h-index
- CC
9
h-index
- DM
7
h-index
- VJ
6
h-index
- SJ
5
h-index
1–5 of 134
Institutions
101
University of Minnesota
Minneapolis, United States
8 h-index
10 publications
633 citations
KU Leuven
Leuven, Belgium
7 h-index
8 publications
624 citations
UNSW Sydney
Sydney, Australia
6 h-index
6 publications
194 citations
Virginia Tech
Blacksburg, United States
6 h-index
10 publications
759 citations
Universidad de Buenos Aires
Buenos Aires, Argentina
5 h-index
6 publications
1.2K citations
Western Michigan University
Kalamazoo, United States
5 h-index
9 publications
261 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
4 publications
516 citations
University of British Columbia
Vancouver, Canada
4 h-index
4 publications
1K citations
1–8 of 101
Venues
- Journal of the American Statistical Association
28 publications · 2.6K citations
24
h-index
- The Annals of Statistics
10 publications · 3K citations
10
h-index
- Statistics & Probability Letters
8 publications · 225 citations
8
h-index
- Communication in Statistics- Theory and Methods
6 publications · 202 citations
6
h-index
- Journal of Statistical Computation and Simulation
JSCS · 3 publications · 48 citations
3
h-index
1–5