Bootstrap Monte Carlo is a computational inference method that belongs to the class of Monte Carlo simulation techniques, distinguished by its use of resampled datasets drawn from empirical observations to estimate the sampling distribution of a statistic through repeated Monte Carlo iterations.
294
Publications
35.6K
Citations
542
Authors
336
Institutions
Publications per year
2017–2026
28
Parents
Publications
294
Estimation and Inference in Econometrics.
Marcus J. Chambers, Russell Davidson, James G. MacKinnon · The Economic Journal · 1994 · 5.6K citations
Randomization, Bootstrap and Monte Carlo Methods in Biology.
Adrienne W. Kemp, Bryan F. J. Manly · Biometrics · 1997 · 1.9K citations
1–5 of 294
Authors
542
- JG
9
h-index
- DN
5
h-index
- RD
5
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- DD
5
h-index
- AC
4
h-index
1–5 of 542
Institutions
336
Queen's University
Kingston, Canada
8 h-index
11 publications
744 citations
University of California, Berkeley
Berkeley, United States
7 h-index
9 publications
816 citations
Stanford University
Stanford, United States
6 h-index
6 publications
564 citations
North Carolina State University
Raleigh, United States
5 h-index
8 publications
460 citations
Carleton University
Ottawa, Canada
5 h-index
6 publications
526 citations
Purdue University West Lafayette
West Lafayette, United States
5 h-index
5 publications
538 citations
Australian National University
Canberra, Australia
5 h-index
7 publications
246 citations
University of California San Diego
San Diego, United States
4 h-index
7 publications
650 citations
1–8 of 336
Venues
- Journal of the American Statistical Association
20 publications · 9.4K citations
18
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- Technometrics
13 publications · 2.5K citations
11
h-index
- Communications in Statistics - Simulation and Computation
9 publications · 664 citations
9
h-index
- Biometrika
8 publications · 308 citations
8
h-index
- Biometrics
8 publications · 3.5K citations
8
h-index
1–5