Bayesian Zero-inflated Models
Bayesian Zero-Inflated Models is a Bayesian statistical modeling framework that belongs to the class of mixture models for count data and is specifically characterized by its incorporation of a dual-process structure to simultaneously account for structural zeros and sampling zeros through prior distributions on model parameters.
78
Publications
3.5K
Citations
249
Authors
165
Institutions
Publications per year
2017–2026
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Swiss Tropical and Public Health Institute, Switzerland
3 publications · 129 citations
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Texas A&M University
College Station, United States
4 h-index
13 publications
180 citations
Swiss Tropical and Public Health Institute
Allschwil, Switzerland
3 h-index
7 publications
299 citations
Universidade de São Paulo
São Paulo, Brazil
3 h-index
5 publications
105 citations
Medical University of South Carolina
Charleston, United States
3 h-index
5 publications
174 citations

University of Auckland
Auckland, New Zealand
3 h-index
4 publications
198 citations
University of South Florida
Tampa, United States
3 h-index
3 publications
62 citations
North Carolina State University
Raleigh, United States
2 h-index
5 publications
691 citations
Indiana University School of Medicine
Indianapolis, United States
2 h-index
3 publications
70 citations
1–8 of 165
5 publications · 186 citations
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3 publications · 82 citations
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3 publications · 187 citations
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2 publications · 52 citations
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2 publications · 137 citations
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