Results 11 to 20 of about 28,569 (299)
Reference priors for non-Normal two-sample problems [PDF]
Test, 1998 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fernández, C., Steel, M.F.J.
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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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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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Parametrizations and reference priors for multinomial decomposable graphical models
Journal of Multivariate Analysis, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Consonni, Guido, Massam, Helene
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Learning Likelihood-Free Reference Priors.
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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BVAR: Bayesian Vector Autoregressions with Hierarchical Prior Selection in R
Journal of Statistical Software, 2021 Vector autoregression (VAR) models are widely used for multivariate time series analysis in macroeconomics, finance, and related fields. Bayesian methods are often employed to deal with their dense parameterization, imposing structure on model ...
Nikolas Kuschnig, Lukas Vashold
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Approximate reference priors for Gaussian random fields [PDF]
Scandinavian Journal of Statistics, 2022 AbstractReference priors are theoretically attractive for the analysis of geostatistical data since they enable automatic Bayesian analysis and have desirable Bayesian and frequentist properties. But their use is hindered by computational hurdles that make their application in practice challenging.
Victor De Oliveira, Zifei Han
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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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Objective bayesian analysis for multiple repairable systems.
PLoS ONE, 2021 This article focus on the analysis of the reliability of multiple identical systems that can have multiple failures over time. A repairable system is defined as a system that can be restored to operating state in the event of a failure.
Amanda M E D'Andrea +8 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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