Results 11 to 20 of about 4,099,878 (253)
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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Model Inference with Reference Priors
, 2011 We describe the application of model inference based on reference priors to two concrete examples in high energy physics: the determination of the CKM matrix parameters rhobar and etabar and the determination of the parameters m_0 and m_1/2 in a simplified version of the CMSSM SUSY model. We show how a 1-dimensional reference posterior can be mapped to
Pierini, Maurizio +3 more
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Learning Likelihood-Free Reference Priors. [PDF]
Simulation modeling offers a flexible approach to constructing high-fidelity synthetic representations of complex real-world systems. However, the increased complexity of such models introduces additional complications, for example when carrying out statistical inference procedures.
Bishop, N +4 more
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Frontiers in Big Data, 2022 For the normal model with a known mean, the Bayes estimation of the variance parameter under the conjugate prior is studied in Lehmann and Casella (1998) and Mao and Tang (2012).
Ying-Ying Zhang +5 more
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Reference priors for the general location-scale modelm [PDF]
Statistics & Probability Letters, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fernández, C., Steel, M.F.J.
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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
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Hellinger Information Matrix and Hellinger Priors
Entropy, 2023 Hellinger information as a local characteristic of parametric distribution families was first introduced in 2011. It is related to the much older concept of the Hellinger distance between two points in a parametric set.
Arkady Shemyakin
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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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On Default Priors for Robust Bayesian Estimation with Divergences
Entropy, 2020 This paper presents objective priors for robust Bayesian estimation against outliers based on divergences. The minimum γ-divergence estimator is well-known to work well in estimation against heavy contamination. The robust Bayesian methods by using quasi-
Tomoyuki Nakagawa, Shintaro Hashimoto
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Multi-Reference Shape Priors for Active Contours [PDF]
International Journal of Computer Vision, 2008 In this paper, we present a new way of constraining the evolution of an active contour with respect to a set of fixed reference shapes. This approach is based on a description of shapes by the Legendre moments computed from their characteristic function. This provides a region-based representation that can handle arbitrary shape topologies.
Foulonneau, Alban +2 more
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