James O. Berger

Duke University

255Publications

65H-index

23.1kCitations

Publications 256

Newest

In Bayesian hypothesis testing and model selection, prior distributions must be chosen carefully. For example, setting arbitrarily large prior scales for location parameters, which is common practice in estimation problems, can lead to undesirable behavior in testing (Lindley's paradox). We study the properties of some restricted type II maximum likelihood (type II ML) priors on regression coefficients. In type II ML, hyperparameters are "estimated" by maximizing the marginal likelihood of a mod...

#1James O. BergerH-Index: 65

#2Woncheol JangH-Index: 9

Last.Ingmar VisserH-Index: 14

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Corrigendum to “Rejection odds and rejection ratios: A proposal for statistical practice in testing hypotheses” [Journal of Mathematical Psychology, 72, 90–103]

#1Maria J. BayarriH-Index: 24

#2Daniel J. BenjaminH-Index: 27

Last.Thomas SellkeH-Index: 16

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#1Daniel J. Benjamin (SC: University of Southern California)H-Index: 27

#2James O. Berger (Duke University)H-Index: 65

ABSTRACTResearchers commonly use p-values to answer the question: How strongly does the evidence favor the alternative hypothesis relative to the null hypothesis? p-Values themselves do not directl...

#1James O. Berger (Duke University)H-Index: 65

#2Leonard A. Smith (University of Oxford)H-Index: 37

The use of models to try to better understand reality is ubiquitous. Models have proven useful in testing our current understanding of reality; for instance, climate models of the 1980s were built ...

#1Maria J. Bayarri (University of Valencia)H-Index: 24

#2James O. Berger (Duke University)H-Index: 65

Last.Ingmar Visser (UvA: University of Amsterdam)H-Index: 14

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We present a new approach to model selection and Bayes factor determination, based on Laplace expansions (as in BIC), which we call Prior-based Bayes Information Criterion (PBIC). In this approach, the Laplace expansion is only done with the likelihood function, and then a suitable prior distribution is chosen to allow exact computation of the (approximate) marginal likelihood arising from the Laplace approximation and the prior. The result is a closed-form expression similar to BIC, but now inv...

#1Mengyang GuH-Index: 4

#2Xiaojing WangH-Index: 8

Last.James O. BergerH-Index: 65

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#1Mengyang GuH-Index: 4

#2Jesus PalomoH-Index: 8

Last.James O. BergerH-Index: 65

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Gaussian stochastic process (GaSP) emulation is a powerful tool for approximating computationally intensive computer models. However, estimation of parameters in the GaSP emulator is a challenging task. No closed-form estimator is available and many numerical problems arise with standard estimates, e.g., the maximum likelihood estimator (MLE). In this package, we implement a marginal posterior mode estimator, for special priors and parameterizations, an estimation method that meets the robust pa...

#1Ksenia N. KyzyurovaH-Index: 1

#2James O. BergerH-Index: 65

Last.Robert L. WolpertH-Index: 27

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Direct coupling of computer models is often difficult for computational and logistical reasons. We propose coupling computer models by linking independently developed Gaussian process emulators (GaSPs) of these models. Linked emulators are developed that are closed form, namely normally distributed with closed form predictive mean and variance functions. These are compared with a more direct emulation strategy, namely running the coupled computer models and directly emulating the system; perhaps...

#1Daniel J. Benjamin (SC: University of Southern California)H-Index: 27

#2James O. Berger (Duke University)H-Index: 65

Last.Valen E. Johnson (SC: University of Southern California)H-Index: 35

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We propose to change the default P-value threshold for statistical significance from 0.05 to 0.005 for claims of new discoveries.

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