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Bayesian Analysis

2009
Abstract This article surveys modern Bayesian methods of estimating statistical models. It first provides an introduction to the Bayesian approach for statistical inference, contrasting it with more conventional approaches. It then explains the Monte Carlo principle and reviews commonly used Markov Chain Monte Carlo (MCMC) methods.
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Electrophysiology Analysis, Bayesian

2014
Bayesian analysis of electrophysiological data refers to the statistical processing of data obtained in electrophysiological experiments (i.e., recordings of action potentials or voltage measurements with electrodes or imaging devices) which utilize methods from Bayesian statistics.
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Bayesian analysis

Abstract The book finishes with a chapter on Bayesian statistics. In a Bayesian analysis a prior distribution and a sample of data are combined to provide a refined posterior distribution. Hence, the posterior distribution can be seen as a fusion between the prior distribution and the observations.
Markus Neuhäuser, Graeme D. Ruxton
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Bayesian statistics and modelling

Nature Reviews Methods Primers, 2021
Rens van de Schoot   +2 more
exaly  

Bayesian Analysis

2022
Nalini Ravishanker   +2 more
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Application of Bayesian approaches in drug development: starting a virtuous cycle

Nature Reviews Drug Discovery, 2023
Stephen J Ruberg, Lisa M Lavange
exaly  

Reconciling Bayesian and Non-Bayesian Analysis

1996
This paper is an attempt to reconcile Bayesian and non-Bayesian approaches to statistical inference, by casting both in terms of a broader formalism. In particular, this paper is an attempt to show that when one extends conventional Bayesian analysis to distinguish the truth from one’s guess for the truth, one gains a broader perspective which allows ...
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Bayesian Analysis

2011
Dominique Haughton, Jonathan Haughton
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