Posterior Normality
Posterior Normality is a theoretical construct in Bayesian statistics that characterizes the asymptotic convergence of a posterior distribution to a normal distribution under regularity conditions, distinguished by its reliance on the concentration of posterior density around the true parameter value as sample size increases.
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114
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79
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2017–2026
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Robert E. Kass, Suresh K. Vaidyanathan · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1992 · 173 citations
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Imperial College London
London, United Kingdom
4 h-index
5 publications
184 citations

Sapienza University of Rome
Rome, Italy
2 h-index
2 publications
195 citations
Educational Testing Service
Princeton, United States
2 h-index
2 publications
145 citations
Purdue University West Lafayette
West Lafayette, United States
2 h-index
3 publications
48 citations

University of British Columbia
Vancouver, Canada
2 h-index
2 publications
44 citations
Université Paris-Sud
Orsay, France
2 h-index
2 publications
106 citations
New York University
New York, United States
2 h-index
2 publications
136 citations
University of Chicago
Chicago, United States
2 h-index
3 publications
74 citations
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13 publications · 1.3K citations
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7 publications · 220 citations
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4 publications · 344 citations
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