Results 211 to 220 of about 1,995,230 (269)
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Probability and Bayesian Statistics.
The Statistician, 1989P. M. Lee, R. Viertl
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Bayesian reaction optimization as a tool for chemical synthesis
Nature, 2021Benjamin J Shields +2 more
exaly
Bayesian statistics and modelling
Nature Reviews Methods Primers, 2021Rens van de Schoot +2 more
exaly
Assessing landslide susceptibility using Bayesian probability-based weight of evidence model
Bulletin of Engineering Geology and the Environment, 2014E. Sujatha +2 more
semanticscholar +1 more source
Bayesian Inference for Lancaster Probabilities [PDF]
, 2008 Inference for bivariate distributions with fixed marginals is very important in applications. When a bayesian approach is followed, the problem of defining a (prior) distribution on a class of probabilities having given marginals arises. We consider the class of Lancaster distributions.
CIFARELLI, DONATO MICHELE +2 more
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Bayesian default probability models
2014This paper proposes a methodology for default probability estimation for low default portfolios, where the statistical inference may become troublesome. The author suggests using logistic regression models with the Bayesian estimation of parameters.
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Determining the conditional probabilities in Bayesian networks
2003Summary: Bayesian networks are used to illustrate how the probability of having a disease can be updated given the results from clinical tests. The problem of diagnosis, that is of determining whether a certain disease is present, \(D\), or absent, \(D'\), based on the result of a medical test, is discussed.
OLMUŞ, Hülya, ERBAŞ, S. Oral
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