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.
Papers
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Integrated likelihood methods for eliminating nuisance parameters
TL;DR: In this paper, the authors review common integrated likelihoods and discuss their strengths and weaknesses relative to other methods, especially those arising from default or non-informative priors.
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The formal definition of reference priors
TL;DR: It is shown how an explicit expression for the reference prior can be obtained under very weak regularity conditions and used to derive new reference priors both analytically and numerically.
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Estimating a Product of Means: Bayesian Analysis with Reference Priors
James O. Berger,José M. Bernardo +1 more
TL;DR: In this article, a reference prior for the problem of estimating the hatching rate of larvae per unit area is proposed, which is based on the product of the mean of the number of larvae hatching per mass and the mean number of masses being hatched per mass.
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Could Fisher, Jeffreys and Neyman Have Agreed on Testing?
TL;DR: The conditional frequentist approach as discussed by the authors is the basis for a methodological unification of the approaches of Fisher, Jeffreys and Neyman, and it is based on the strength of evidence in the data.
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Computer model validation with functional output
Maria J. Bayarri,James O. Berger,John A. Cafeo,Gonzalo García-Donato,F. Liu,Jesus Palomo,R. J. Parthasarathy,Rui Paulo,Jerome Sacks,Daniel C. I. Walsh +9 more
TL;DR: A six-step process for computer model validation is set out in Bayarri et al. (2007) based on comparison of computer model runs with field data of the process being modeled, which is particularly suited to treating the major issues associated with the validation process.