Robust Bayesian Modeling
Robust Bayesian Modeling is a Bayesian modeling framework that explicitly accounts for potential deviations from assumed model specifications, such as outliers, model misspecifications, or influential observations, by incorporating flexible priors, heavy-tailed distributions, or sensitivity analyses to ensure inferential reliability across a range of plausible data-generating mechanisms.
265
Publications
16.6K
Citations
597
Authors
344
Institutions
Publications per year
2017–2026
71
Parents
265
An overview of robust Bayesian analysis
James O. Berger, Elı́as Moreno, Luis R. Pericchi et al. · Test · 1994 · 610 citations
1–5 of 265
597
10
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Istituto di Matematica Applicata e Tecnologie Informatiche, Italy
8 publications · 838 citations
8
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6
h-index
5
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5
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1–5 of 597
344
Purdue University West Lafayette
West Lafayette, United States
10 h-index
12 publications
1.8K citations
Carnegie Mellon University
Pittsburgh, United States
8 h-index
19 publications
948 citations

Universidad de Granada
Granada, Spain
7 h-index
9 publications
1.1K citations
Istituto di Matematica Applicata e Tecnologie Informatiche
Pavia, Italy
6 h-index
7 publications
164 citations
Duke University
Durham, United States
6 h-index
11 publications
565 citations
University of Florida
Gainesville, United States
5 h-index
6 publications
238 citations

SGH Warsaw School of Economics
Warsaw, Poland
5 h-index
5 publications
186 citations
University of Washington
Seattle, United States
5 h-index
13 publications
1.9K citations
1–8 of 344
18 publications · 841 citations
15
h-index
13 publications · 700 citations
11
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11 publications · 1.1K citations
11
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Repository · 13 publications · 674 citations
11
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8 publications · 254 citations
8
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1–5