J
James O. Berger
Researcher at Duke University
Publications - 241
Citations - 39178
James O. Berger is an academic researcher from Duke University. The author has contributed to research in topics: Prior probability & Bayesian probability. The author has an hindex of 71, co-authored 241 publications receiving 36488 citations. Previous affiliations of James O. Berger include University of Valencia & University College London.
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Journal ArticleDOI
Overall Objective Priors
TL;DR: In this paper, the authors consider three methods for selecting a single objective prior and study whether or not the resulting prior is a reasonable overall prior in a variety of problems including the multinomial problem.
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Statistical Interpretation of the RV144 HIV Vaccine Efficacy Trial in Thailand: A Case Study for Statistical Issues in Efficacy Trials
Peter B. Gilbert,James O. Berger,Donald Stablein,Stephen Becker,Max Essex,Scott M. Hammer,Jerome H. Kim,Victor DeGruttola +7 more
TL;DR: Bayesian statistics, which provide clearly interpretable statements about probabilities that the vaccine efficacy takes certain values, provide more information for weighing the evidence about efficacy than do frequentist statistics alone.
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Objective priors for the bivariate normal model
James O. Berger,Dongchu Sun +1 more
TL;DR: In this paper, the authors investigate the availability of objective priors that yield exact frequentist inferences for many functions of the bivariate normal parameters, including the correlation coefficient, and make recommendations as to optimal objective prior for a variety of inferences involving the biannual distribution.
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Choice of hierarchical priors: admissibility in estimation of normal means
TL;DR: In this paper, hierarchical priors for normal means are categorized in terms of admissibility and inadmissibility of resulting estimators for a quite general scenario, and the conditions under which the (generally improper) priors result in proper posteriors.
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Estimating Shape Constrained Functions Using Gaussian Processes
Xiaojing Wang,James O. Berger +1 more
TL;DR: The possibilities and challenges of introducing shape constraints through this device are explored and illustrated through simulations and two real data examples.