Adaptive Robust Estimation
Adaptive Robust Estimation is a statistical methodology that belongs to the class of robust estimation techniques, distinguished by its ability to automatically adjust its estimating functions or tuning parameters based on the data structure and contamination level to achieve optimal trade-offs between efficiency and robustness.
78
Publications
2.9K
Citations
204
Authors
131
Institutions
Publications per year
2017–2026
27
Parents
78
Qiang Sun, Wen‐Xin Zhou, Jianqing Fan · Journal of the American Statistical Association · 2018 · 305 citations · Full text
An Efficient and Robust Adaptive Estimator of Location
Rudolf Beran · The Annals of Statistics · 1978 · 108 citations · Full text
1–5 of 78
204
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Korea Advanced Institute of Science and Technology, South Korea
3 publications · 47 citations
3
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3
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2
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2
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1–5 of 204
131
Princeton University
Princeton, United States
4 h-index
4 publications
386 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
3 h-index
5 publications
207 citations

Harbin Institute of Technology
Harbin, China
3 h-index
7 publications
196 citations

Newcastle University
Newcastle upon Tyne, United Kingdom
2 h-index
6 publications
88 citations
Brigham Young University
Provo, United States
2 h-index
3 publications
85 citations
Tsinghua University
Beijing, China
2 h-index
3 publications
67 citations

The University of Sydney
Sydney, Australia
2 h-index
3 publications
70 citations

University of Edinburgh
Edinburgh, United Kingdom
2 h-index
2 publications
85 citations
1–8 of 131
4 publications · 374 citations
4
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3 publications · 360 citations
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3 publications · 75 citations
3
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2 publications · 82 citations
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2 publications · 74 citations
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