Model Uncertainty
Model Uncertainty is the epistemic uncertainty arising from the selection of a statistical or machine learning model structure and its parameters, reflecting the inadequacy of the chosen model to fully capture the underlying data-generating process due to limitations in model form, assumptions, or representational capacity.
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Bayesian Model Selection in Social Research
Adrian E. Raftery · Sociological Methodology · 1995 · 6.9K citations
Computing, Biostatistics, Sociology +17
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European Centre for Medium-Range Weather Forecasts, United Kingdom
15 publications · 1.7K citations
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Centre National de la Recherche Scientifique
Paris, France
37 h-index
146 publications
11.3K citations
ETH Zurich
Zurich, Switzerland
36 h-index
129 publications
16.8K citations
University of California, Berkeley
Berkeley, United States
34 h-index
112 publications
8.1K citations
University of Cambridge
Cambridge, United Kingdom
33 h-index
86 publications
26.3K citations
University of Washington
Seattle, United States
32 h-index
64 publications
20.3K citations
Massachusetts Institute of Technology
Cambridge, United States
31 h-index
112 publications
8.9K citations
University of Oxford
Oxford, United Kingdom
31 h-index
112 publications
8.7K citations
Met Office
Exeter, United Kingdom
30 h-index
90 publications
7.4K citations
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84 publications · 6.7K citations
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Repository · 107 publications · 4.1K citations
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Repository · 90 publications · 12.1K citations
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40 publications · 3.6K citations
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37 publications · 3.7K citations
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