Results 21 to 30 of about 1,707,051 (309)
On the effect of prior assumptions in Bayesian model averaging with applications to growth regresssion [PDF]
, 2007 We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressor and relatively limited numbers of observations.
Eduardo Ley +4 more
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Reference priors for high energy physics [PDF]
Physical Review D, 2010 Bayesian inferences in high energy physics often use uniform prior distributions for parameters about which little or no information is available before data are collected. The resulting posterior distributions are therefore sensitive to the choice of parametrization for the problem and may even be improper if this choice is not carefully considered ...
Demortier, Luc +2 more
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The Prior Can Often Only Be Understood in the Context of the Likelihood
Entropy, 2017 A key sticking point of Bayesian analysis is the choice of prior distribution, and there is a vast literature on potential defaults including uniform priors, Jeffreys’ priors, reference priors, maximum entropy priors, and weakly informative priors. These
Andrew Gelman +2 more
doaj +1 more source
The formal definition of reference priors
The Annals of Statistics, 2009 Reference analysis produces objective Bayesian inference, in the sense that inferential statements depend only on the assumed model and the available data, and the prior distribution used to make an inference is least informative in a certain information-theoretic sense.
Berger, James O. +2 more
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Reference priors for discrete graphical models [PDF]
Biometrika, 2006 SUMMARY The combination of graphical models and reference analysis represents a powerful tool for Bayesian inference in highly multivariate settings. It is typically difficult to derive reference priors in complex problems. In this paper we present a suitable mixed para meterisation for a discrete decomposable graphical model and derive the ...
Consonni, Guido, Leucari, Valentina
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On the implementation of local probability matching priors for interest parameters [PDF]
, 2005 Probability matching priors are priors for which the posterior probabilities of certain specified sets are exactly or approximately equal to their coverage probabilities.
Sweeting, TJ, Trevor J. Sweeting
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Improved Bayesian Inferences for Right-Censored Birnbaum–Saunders Data
MathematicsThis work focuses on making Bayesian inferences for the two-parameter Birnbaum–Saunders (BS) distribution in the presence of right-censored data. A flexible Gibbs sampler is employed to handle the censored BS data in this Bayesian work that relies on ...
Kalanka P. Jayalath
doaj +1 more source
Convolutional Neural Network‐Based Adaptive Localization for an Ensemble Kalman Filter
Journal of Advances in Modeling Earth Systems, 2023 Flow‐dependent background error covariances estimated from short‐term ensemble forecasts suffer from sampling errors due to limited ensemble sizes. Covariance localization is often used to mitigate the sampling errors, especially for high dimensional ...
Zhongrui Wang +4 more
doaj +1 more source
Population Pharmacokinetic Model of Adalimumab Based on Prior Information Using Real World Data
Biomedicines, 2023 Adalimumab is a fully human monoclonal antibody used for the treatment of inflammatory bowel disease (IBD). Due to its considerably variable pharmacokinetics and the risk of developing antibodies against adalimumab, it is highly recommended to use a ...
Silvia Marquez-Megias +3 more
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Estimation of a Covariance Matrix Using the Reference Prior
The Annals of Statistics, 1994 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yang, Ruoyong, Berger, James O.
openaire +2 more sources