Model-based Resampling
Model-Based Resampling is a resampling technique that generates new samples from an estimated parametric or semi-parametric model of the data distribution, as opposed to relying solely on empirical data repetition or permutation.
36
Publications
4.4K
Citations
90
Authors
64
Institutions
Publications per year
2017–2026
8
Parents
36
Comparing network structures on three aspects: A permutation test.
Claudia D. van Borkulo, Riet van Bork, Lynn Boschloo et al. · Psychological Methods · 2022 · 1.3K citations · Full text
Reshaping Data with the reshape Package
Hadley Wickham · 2007 · 428 citations · Full text
Resampling Methods: A Practical Guide to Data Analysis
Yogendra P. Chaubey, Phillip I. Good · Technometrics · 2000 · 405 citations
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W.E. Upjohn Institute for Employment Research, United States
2 publications · 514 citations
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1
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64

Concordia University
Montreal, Canada
3 h-index
3 publications
557 citations

Utah State University
Logan, United States
2 h-index
2 publications
83 citations
University of Wisconsin–Madison
Madison, United States
2 h-index
2 publications
83 citations
Hydro-Québec
Montreal, Canada
1 h-index
1 publications
47 citations

Centre for Mental Health
London, United Kingdom
1 h-index
1 publications
1.3K citations
University of Aveiro
Aveiro, Portugal
1 h-index
1 publications
12 citations
Ministry of Education
Wellington, New Zealand
1 h-index
1 publications
10 citations

Bar-Ilan University
Ramat Gan, Israel
1 h-index
1 publications
30 citations
1–8 of 64
5 publications · 365 citations
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4 publications · 1.5K citations
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JDSA · 1 publications · 64 citations
1
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1 publications · 30 citations
1
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1 publications · 36 citations
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