Decision-theoretic Model Averaging
Decision-Theoretic Model Averaging is a Bayesian model averaging framework that formalizes model uncertainty quantification and parameter estimation within a decision-theoretic paradigm by optimally combining posterior model predictions according to a specified loss function and prior beliefs.
21
Publications
1.3K
Citations
60
Authors
52
Institutions
Publications per year
2017–2026
9
Parents
21
David McAllester · 1999 · 372 citations
David T. Levy, Ron Borland, Andrea C. Villanti et al. · Nicotine & Tobacco Research · 2016 · 112 citations · Full text
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Chinese University of Hong Kong, Hong Kong SAR China
1 publications · 35 citations
1
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1–5 of 60
52

University of Warsaw
Warsaw, Poland
1 h-index
1 publications
18 citations
Victorian Health Promotion Foundation
Carlton, Australia
1 h-index
1 publications
112 citations
University of Kent
Canterbury, United Kingdom
1 h-index
1 publications
167 citations

Transport and Telecommunication Institute
Riga, Latvia
1 h-index
1 publications
13 citations

Georgetown University Medical Center
Washington, United States
1 h-index
4 publications
448 citations
AT&T (United States)
Bedminster, United States
1 h-index
1 publications
372 citations
Sensory Cloud (United States)
Boston, United States
1 h-index
1 publications
27 citations

Imperial College London
London, United Kingdom
1 h-index
1 publications
81 citations
1–8 of 52
JASA · 1 publications · 14 citations
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1 publications · 79 citations
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1 publications · 35 citations
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1 publications · 22 citations
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Repository · 1 publications · 81 citations
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