Bootstrap Variance Component Inference
Bootstrap Variance Component Inference is a statistical methodology that uses resampling techniques to estimate the variability of variance components in hierarchical or mixed-effects models by repeatedly sampling from the observed data to approximate the sampling distribution of the component estimates.
6
Publications
253
Citations
10
Authors
12
Institutions
Publications per year
2017–2026
0
Parents
6
On bootstrap inference in cointegrating regressions
Zacharias Psaradakis · Economics Letters · 2001 · 12 citations
1–5 of 6
10
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Center for Devices and Radiological Health, United States
1 publications · 126 citations
1
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Center for Devices and Radiological Health, United States
1 publications · 126 citations
1
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1–5 of 10
12

Birkbeck, University of London
London, United Kingdom
1 h-index
1 publications
12 citations
Office of Science
Washington, United States
1 h-index
2 publications
252 citations
Texas A&M University
College Station, United States
1 h-index
1 publications
76 citations
United States Food and Drug Administration
Silver Spring, United States
1 h-index
3 publications
378 citations

Northern Arizona University
Flagstaff, United States
1 h-index
1 publications
10 citations
Département Génétique Animale
Castanet-Tolosan, France
1 h-index
2 publications
28 citations
Center for Devices and Radiological Health
Rockville, United States
1 h-index
3 publications
378 citations
London School of Economics and Political Science
London, United Kingdom
1 h-index
1 publications
12 citations
1–8 of 12
JABES · 1 publications · 10 citations
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1 publications · 126 citations
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1 publications · 15 citations
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1 publications · 14 citations
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1 publications · 12 citations
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