Bayesian Nonparametric Sample Size
Bayesian Nonparametric Sample Size is a statistical methodology that determines the minimum sample size required for a study using Bayesian nonparametric models, which avoid rigid parametric assumptions by placing priors on infinite-dimensional spaces to flexibly model unknown distributions while incorporating decision-theoretic or precision-based criteria for sample size justification.
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2017–2026
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A Bayesian nonparametric method for prediction in EST analysis
Antonio Lijoi, Ramsés H. Mena, Igor Prünster · BMC Bioinformatics · 2007 · 32 citations · Full text
Natural Sciences, Biology, Genetics +13
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University of California, Irvine
Irvine, United States
1 h-index
1 publications
10 citations
Collegio Carlo Alberto
Moncalieri, Italy
1 h-index
1 publications
32 citations
University of Pavia
Pavia, Italy
1 h-index
1 publications
32 citations
Universidad Nacional Autónoma de México
Mexico City, Mexico
1 h-index
1 publications
32 citations

University of Turin
Turin, Italy
1 h-index
1 publications
32 citations
Oregon State University
Corvallis, United States
1 h-index
1 publications
10 citations
Baylor Scott & White Health
Dallas, United States
1 h-index
1 publications
10 citations
National Research Council
Rome, Italy
1 h-index
1 publications
32 citations
1–8 of 9
1 publications · 10 citations
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1 publications · 15 citations
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1 publications · 32 citations
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1 publications · 21 citations
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