Prior Robustness is a property of Bayesian inference that characterizes the sensitivity of posterior conclusions to variations in the specification of the prior distribution, distinguishing it from related methodological concerns by focusing specifically on the stability of inferences under plausible alternative prior assumptions.
265
Publications
15K
Citations
565
Authors
298
Institutions
Publications per year
2017–2026
44
Variants
Prior Sensitivity
Parents
Publications
265
1–5 of 265
Authors
565
- JO
8
h-index
- EM
5
h-index
- LW
5
h-index
- AO
4
h-index
- LW
4
h-index
1–5 of 565
Institutions
298
Carnegie Mellon University
Pittsburgh, United States
10 h-index
18 publications
662 citations
Purdue University West Lafayette
West Lafayette, United States
9 h-index
10 publications
636 citations
Universidad de Granada
Granada, Spain
7 h-index
8 publications
236 citations
University of Toronto
Toronto, Canada
6 h-index
12 publications
256 citations
University of California, Davis
Davis, United States
5 h-index
11 publications
315 citations
Duke University
Durham, United States
5 h-index
6 publications
242 citations
Decision Sciences (United States)
Fort Walton Beach, United States
5 h-index
6 publications
382 citations
Harvard University
Cambridge, United States
4 h-index
4 publications
95 citations
1–8 of 298
Venues
- Journal of the American Statistical Association
16 publications · 602 citations
12
h-index
- The Annals of Statistics
12 publications · 1K citations
11
h-index
- Journal of Statistical Planning and Inference
10 publications · 603 citations
10
h-index
- Canadian Journal of Statistics
CJS · 8 publications · 222 citations
8
h-index
- Biometrika
8 publications · 415 citations
8
h-index
1–5