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
General Admissibility and Inadmissibility Results for Estimation in a Control Problem
TL;DR: In this paper, the authors consider a control problem which, in canonical form, is the problem of estimating the probability of an observation from a $p-variate normal distribution with unknown mean and identity covariance matrix.
Journal ArticleDOI
Bayesian analysis of the covariance matrix of a multivariate normal distribution with a new class of priors
TL;DR: In this article, a new class of priors for the covariance matrix, including both inverse Wishart and reference priors as special cases, is proposed, which do not force eigenvalues apart, and extensive comparison of these priors is undertaken, with the new priors seeming to have considerably better performance.
Book ChapterDOI
Incorporating prior information in minimax estimation of the mean of a gaussian process
TL;DR: In this paper, a more complicated expansion of the Karhunen-Loeve expansion is developed in which the desired minimax estimator is also derived, allowing use of all the prior information in selecting a minimax estimate.
Journal ArticleDOI
Prior-based Bayesian information criterion
TL;DR: Prior-based Bayes Information Criterion (PBIC) as mentioned in this paper is a new approach to model selection and Bayes factor determination, based on Laplace expansions, which is called Prior-based BIC, and also incorporates the idea that different parameters can have different effective sample sizes (whereas BIC only allows one overall sample size n).