Bootstrap Bias Estimation
Bootstrap Bias Estimation is a resampling-based statistical method that quantifies the systematic deviation between a sample estimator and its population parameter by comparing the mean of bootstrap replications to the original sample estimate.
264
Publications
39.9K
Citations
477
Authors
304
Institutions
Publications per year
2017–2026
38
Parents
264
1–5 of 264
477
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304

Australian National University
Canberra, Australia
15 h-index
24 publications
2.2K citations
Stanford University
Stanford, United States
7 h-index
7 publications
3K citations

University of Hong Kong
Pok Fu Lam, Hong Kong
6 h-index
7 publications
805 citations

Ghent University
Ghent, Belgium
5 h-index
13 publications
1.3K citations
University of Michigan
Ann Arbor, United States
5 h-index
7 publications
858 citations
University of Iowa
Iowa City, United States
4 h-index
4 publications
776 citations
University of Florida
Gainesville, United States
4 h-index
7 publications
491 citations
Iowa State University
Ames, United States
4 h-index
4 publications
475 citations
1–8 of 304
15 publications · 3.2K citations
15
h-index
17 publications · 1.4K citations
14
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13 publications · 3.8K citations
12
h-index
9 publications · 588 citations
9
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JSCS · 9 publications · 417 citations
9
h-index
1–5