Nonparametric Confidence Intervals is a statistical method for constructing interval estimates of a population parameter that does not rely on assumptions about the underlying distribution of the data, distinguishing it from parametric approaches by using data-driven techniques such as bootstrapping or rank-based procedures.
346
Publications
54.4K
Citations
664
Authors
360
Institutions
Publications per year
2017–2026
51
Variants
Distribution-free Confidence Intervals
Parents
Publications
346
Better Bootstrap Confidence Intervals
Bradley Efron · Journal of the American Statistical Association · 1987 · 3.3K citations
1–5 of 346
Authors
664
- BE
10
h-index
- FK
6
h-index
- PH
6
h-index
- JP
5
h-index
- PKPranab Kumar Sen
University of North Carolina at Chapel Hill, United States
5 publications · 14.8K citations
5
h-index
1–5 of 664
Institutions
360
Stanford University
Stanford, United States
17 h-index
23 publications
6.7K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
9 h-index
18 publications
15.5K citations
University of California, Berkeley
Berkeley, United States
8 h-index
14 publications
678 citations
University of Michigan
Ann Arbor, United States
8 h-index
14 publications
8.3K citations
University of Göttingen
Göttingen, Germany
7 h-index
7 publications
470 citations
Columbia University
New York, United States
6 h-index
9 publications
555 citations
Cornell University
Ithaca, United States
6 h-index
7 publications
211 citations
McMaster University
Hamilton, Canada
6 h-index
9 publications
185 citations
1–8 of 360
Venues
- Journal of the American Statistical Association
40 publications · 21.6K citations
28
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- The Annals of Statistics
28 publications · 3.6K citations
27
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- Biometrika
16 publications · 1.2K citations
14
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- Biometrics
12 publications · 1.5K citations
12
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- Statistics in Medicine
8 publications · 702 citations
8
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1–5