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Robust Bayesian hypothesis testing with the hierarchical EZ-DDM. [PDF]
Behav Res MethodsChávez De la Peña AF +2 more
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Efficient Estimation Methods for the QR Distribution with Type-II Censored Data: An Empirical Validation on Lung Cancer Prognosis. [PDF]
Entropy (Basel)Ramzan Q, Amin M, Alghamdi S, Alharbi R.
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, 2010 Bayesian statistics 478 How Bayesian methods work 480 Prior distributions 482 Likelihood; posterior distributions 484 Summarizing and presenting results 486 Using Bayesian analyses in medicine 488
Janet L. Peacock, Philip J. Peacock
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The Development of Bayesian Statistics
Journal of the Indian Institute of Science, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Bayesian statistics for parasitologists
Trends in Parasitology, 2004Bayesian statistical methods are increasingly being used in the analysis of parasitological data. Here, the basis of differences between the Bayesian method and the classical or frequentist approach to statistical inference is explained. This is illustrated with practical implications of Bayesian analyses using prevalence estimation of strongyloidiasis
María-Gloria, Basáñez +4 more
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Overview of Bayesian Statistics
Evaluation Review, 2020Bayesian statistics is becoming a popular approach to handling complex statistical modeling. This special issue of Evaluation Review features several Bayesian contributions. In this overview, I present the basics of Bayesian inference. Bayesian statistics is based on the principle that parameters have a distribution of beliefs about them that behave ...
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The Bayesian score statistic [PDF]
, 2000 We propose a novel Bayesian test under a (noninformative) Jeffreys'priorspecification. We check whether the fixed scalar value of the so-calledBayesian Score Statistic (BSS) under the null hypothesis is aplausiblerealization from its known and standardized distribution under thealternative. Unlike highest posterior density regions the BSS isinvariantto
Kleibergen, F.R., Kleijn, R., Paap, R.
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Understanding Bayesian Statistics
Journal of Spinal Disorders & Techniques, 2015Modern computing power has given us the ability to approach statistical questions in a manner which was previously impossible because of the time-consuming nature of the calculations required. Computer power has enabled the use of Bayesian inference techniques, based on 18th century theory, to frame statistical questions in probability.
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Analytical Methods, 2012
While data evaluation methods based on significance tests are familiar to analytical scientists, it is not so widely appreciated that alternative Bayesian methods are now also commonly used in a range of fields. This Technical Brief outlines some examples of the importance of Bayesian methods in a variety of areas of applied analytical science.
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While data evaluation methods based on significance tests are familiar to analytical scientists, it is not so widely appreciated that alternative Bayesian methods are now also commonly used in a range of fields. This Technical Brief outlines some examples of the importance of Bayesian methods in a variety of areas of applied analytical science.
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