Bayesian Smoothing Priors
Bayesian Smoothing Priors is a class of informative prior distributions in Bayesian categorical data analysis that incorporate regularization by shrinking extreme probability estimates toward more plausible values, thereby reducing overfitting and improving posterior stability in sparse data settings.
8
Publications
366
Citations
17
Authors
12
Institutions
Publications per year
2017–2026
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8
1–5 of 8
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Norwegian University of Science and Technology
Trondheim, Norway
2 h-index
4 publications
264 citations
University of Copenhagen
Copenhagen, Denmark
1 h-index
2 publications
92 citations
University of California, Los Angeles
Los Angeles, United States
1 h-index
1 publications
28 citations
University of Lisbon
Lisbon, Portugal
1 h-index
5 publications
195 citations
The Institute of Statistical Mathematics
Tokyo, Japan
1 h-index
2 publications
92 citations
University of Zurich
Zurich, Switzerland
1 h-index
3 publications
225 citations

Universidade Nova de Lisboa
Lisbon, Portugal
1 h-index
2 publications
78 citations

Aarhus University
Aarhus, Denmark
1 h-index
1 publications
46 citations
1–8 of 12
Repository · 2 publications · 45 citations
2
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Repository · 1 publications · 75 citations
1
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1 publications · 77 citations
1
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1 publications · 56 citations
1
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1 publications · 28 citations
1
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