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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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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 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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Systematic search of Bayesian statistics in the field of psychotraumatology. [PDF]
Eur J Psychotraumatol, 2017 In many different disciplines there is a recent increase in interest of Bayesian analysis. Bayesian methods implement Bayes' theorem, which states that prior beliefs are updated with data, and this process produces updated beliefs about model parameters.
van de Schoot R, Schalken N, Olff M.
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Method for adjusting results of pharmacoeconomic studies from country to country using Bayesian statistics [PDF]
Hospital Pharmacology, 2021 Introduction: Key problems when transferring results of pharmacoeconomic studies between countries are: relative infrequency of observational design, utilization of unreliable estimates of input parameters in many of modelling studies, not reporting ...
Janković Slobodan M. +2 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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Statistical Information: A Bayesian Perspective [PDF]
Entropy, 2011 We explore the meaning of information about quantities of interest. Our approach is divided in two scenarios: the analysis of observations and the planning of an experiment. First, we review the Sufficiency, Conditionality and Likelihood principles and how they relate to trivial experiments.
Rafael Bassi Stern +1 more
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