Balanced Bootstrap
Balanced Bootstrap is a resampling technique that belongs to the class of bootstrap methods, distinguished by its systematic replication of each observation an equal number of times across all bootstrap samples to ensure balanced representation and reduce Monte Carlo variance.
19
Publications
1.1K
Citations
35
Authors
25
Institutions
Publications per year
2017–2026
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University of California, Berkeley
Berkeley, United States
2 h-index
2 publications
121 citations

Australian National University
Canberra, Australia
2 h-index
2 publications
36 citations
Brown University
Providence, United States
1 h-index
1 publications
72 citations
University of Florida
Gainesville, United States
1 h-index
1 publications
15 citations
Tufts University
Medford, United States
1 h-index
2 publications
372 citations

University of Alberta
Edmonton, Canada
1 h-index
3 publications
45 citations
John Brown University
Siloam Springs, United States
1 h-index
2 publications
144 citations
University of Wisconsin–Madison
Madison, United States
1 h-index
1 publications
59 citations
1–8 of 25
2 publications · 121 citations
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2 publications · 95 citations
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1 publications · 59 citations
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1 publications · 183 citations
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1 publications · 90 citations
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