Predictive Posterior Analysis
Predictive Posterior Analysis is a statistical framework within Bayesian inference that characterizes the distribution of future observations by integrating over the posterior distribution of model parameters, thereby distinguishing itself from prior predictive methods through its dependence on observed data to update parameter uncertainty.
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8.6K
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333
Authors
213
Institutions
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2017–2026
30
Parents
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Model choice: a minimum posterior predictive loss approach
Alan E. Gelfand · Biometrika · 1998 · 740 citations
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University of Michigan
Ann Arbor, United States
6 h-index
11 publications
544 citations
The Ohio State University
Columbus, United States
5 h-index
7 publications
266 citations
Educational Testing Service
Princeton, United States
4 h-index
8 publications
1.4K citations
Duke University
Durham, United States
4 h-index
5 publications
378 citations

University of Exeter
Exeter, United Kingdom
3 h-index
6 publications
246 citations
United States Geological Survey
Reston, United States
3 h-index
3 publications
264 citations

University of Hawaii System
Honolulu, United States
3 h-index
4 publications
310 citations

University of Edinburgh
Edinburgh, United Kingdom
3 h-index
5 publications
427 citations
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8 publications · 487 citations
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7 publications · 826 citations
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Repository · 3 publications · 53 citations
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3 publications · 215 citations
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