Robust Confidence Intervals
Robust Confidence Intervals is a statistical inference method that belongs to the class of confidence interval estimation techniques and is distinguished by its ability to maintain valid coverage and accuracy even under violations of standard distributional assumptions, such as the presence of outliers or non-normality in the data.
155
Publications
28K
Citations
273
Authors
181
Institutions
Publications per year
2017–2026
32
155
1–5 of 155
273
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h-index
5
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5
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4
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181
University of Southern California
Los Angeles, United States
12 h-index
15 publications
651 citations

University of British Columbia
Vancouver, Canada
6 h-index
9 publications
759 citations
University of Michigan
Ann Arbor, United States
5 h-index
9 publications
8.2K citations
University of Miami
Coral Gables, United States
5 h-index
7 publications
4.5K citations
California Southern University
Chandler, United States
4 h-index
4 publications
149 citations

Universidade Federal de Pernambuco
Recife, Brazil
4 h-index
4 publications
192 citations
University of California, Berkeley
Berkeley, United States
4 h-index
5 publications
331 citations
Harvard University
Cambridge, United States
4 h-index
6 publications
219 citations
1–8 of 181
14 publications · 15.3K citations
12
h-index
9 publications · 428 citations
9
h-index
6 publications · 492 citations
6
h-index
4 publications · 3.1K citations
4
h-index
4 publications · 114 citations
4
h-index
1–5