Results 11 to 20 of about 549,710 (321)

Bayesian Uncertainty Quantification for Channelized Reservoirs via Reduced Dimensional Parameterization

open access: yesMathematics, 2021
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
doaj   +1 more source

Software for Bayesian Statistics

open access: yesJournal of Statistical Software, 2021
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
doaj   +1 more source

Bayesian statistics

open access: yesScholarpedia, 2009
© 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
  +7 more sources

Bayesian Statistics

open access: yes, 2021
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
openaire   +2 more sources

Bayesian Structure Learning and Sampling of Bayesian Networks with the R Package BiDAG

open access: yesJournal of Statistical Software, 2023
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
doaj   +1 more source

Bayes in action in deep learning and dictionary learning [PDF]

open access: yesESAIM: Proceedings and Surveys, 2023
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
doaj   +1 more source

Bayesian Model Averaging Using Power-Expected-Posterior Priors

open access: yesEconometrics, 2020
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
doaj   +1 more source

Comparing Bayesian Statistics and Frequentist Statistics in Serious Games Research

open access: yesInternational Journal of Serious Games, 2021
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
doaj   +1 more source

Cosmological Parameter Inference with Bayesian Statistics

open access: yesUniverse, 2021
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
doaj   +1 more source

Discussion of "Frequentist coverage of adaptive nonparametric Bayesian credible sets" [PDF]

open access: yes, 2015
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
core   +5 more sources

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