Results 11 to 20 of about 2,194,170 (284)
A comparative review of dimension reduction methods in approximate Bayesian computation [PDF]
, 2013 Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions.
Prangle, D. +6 more
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Mathematics, 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
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Scholarpedia, 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 ...
David J. Spiegelhalter, Kenneth M. Rice
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Bayesian statistics and modelling [PDF]
, 2021 Bayesian statistics is an approach to data analysis and parameter estimation based on Bayes’ Theorem. This Primer describes the stages involved in Bayesian analysis, from specifying the prior and data models, to deriving inference, model checking and ...
Kramer, Bianca +13 more
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Bayesian Model Averaging Using Power-Expected-Posterior Priors
Econometrics, 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
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Bayesian Structure Learning and Sampling of Bayesian Networks with the R Package BiDAG
Journal 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
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Comparing Bayesian Statistics and Frequentist Statistics in Serious Games Research
International 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
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Cosmological Parameter Inference with Bayesian Statistics
Universe, 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
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Estimating COVID-19 excess mortality during and after the pandemic: A Bayesian model, with an application to New Zealand [PDF]
Demographic ResearchBACKGROUND: COVID-19 excess deaths are a standard measure of the effects of COVID on mortality. They are defined as the difference between actual death counts and the counts that would have been expected in the absence of the pandemic.
John Bryant +4 more
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Bayesian Mode Regression [PDF]
, 2014 This article has been made available through the Brunel Open Access Publishing Fund.Like mean, quantile and variance, mode is also an important measure of central tendency of a distribution.
Yu, K, Aristodemou, K, Lu, Z
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