Results 11 to 20 of about 549,710 (321)
In this article, we study uncertainty quantification for flows in heterogeneous porous media. We use a Bayesian approach where the solution to the inverse problem is given by the posterior distribution of the permeability field given the flow and ...
Anirban Mondal, Jia Wei
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Software for Bayesian Statistics
In this summary we introduce the papers published in the special issue on Bayesian statistics. This special issue comprises 20 papers on Bayesian statistics and Bayesian inference on different topics such as general packages for hierarchical linear model
Michela Cameletti, Virgilio Gómez-Rubio
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© 2012 Springer Science+Business Media, LLC. All rights reserved. Article Outline: Glossary Definition of the Subject and Introduction The Bayesian Statistical Paradigm Three Examples Comparison with the Frequentist Statistical Paradigm Future Directions ...
Kenneth Rice, David Spiegelhalter
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Abstract The chapter “Bayesian Statistics” gives a brief overview of the Bayesian approach to statistical analysis. It starts off by examining the difference between frequentist statistics and Bayesian statistics. Next, it introduces Bayes’ theorem and explains how the theorem is used in statistics and model selection, with the ...
Göran Kauermann +2 more
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Bayesian Structure Learning and Sampling of Bayesian Networks with the R Package BiDAG
The R package BiDAG implements Markov chain Monte Carlo (MCMC) methods for structure learning and sampling of Bayesian networks. The package includes tools to search for a maximum a posteriori (MAP) graph and to sample graphs from the posterior ...
Polina Suter +3 more
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Bayes in action in deep learning and dictionary learning [PDF]
This article summarizes some recent works and associated challenges in the field of Bayesian statistics that were presented during the Journées MAS 2020.
Arbel Julyan +5 more
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Bayesian Model Averaging Using Power-Expected-Posterior Priors
This paper focuses on the Bayesian model average (BMA) using the power–expected– posterior prior in objective Bayesian variable selection under normal linear models.
Dimitris Fouskakis, Ioannis Ntzoufras
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Comparing Bayesian Statistics and Frequentist Statistics in Serious Games Research
This article presents three empirical studies on the effectiveness of serious games for learning and motivation, while it compares the results arising from Frequentist (classical) Statistics with those from Bayesian Statistics.
Wim Westera
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Cosmological Parameter Inference with Bayesian Statistics
Bayesian statistics and Markov Chain Monte Carlo (MCMC) algorithms have found their place in the field of Cosmology. They have become important mathematical and numerical tools, especially in parameter estimation and model comparison.
Luis E. Padilla +3 more
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Discussion of "Frequentist coverage of adaptive nonparametric Bayesian credible sets" [PDF]
Discussion of "Frequentist coverage of adaptive nonparametric Bayesian credible sets" by Szab\'o, van der Vaart and van Zanten [arXiv:1310.4489v5].Comment: Published at http://dx.doi.org/10.1214/15-AOS1270D in the Annals of Statistics (http://www ...
Low, Mark G., Ma, Zongming
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