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Journal ArticleDOI

Fiducial Distributions and Bayes' Theorem

Dennis V. Lindley
- 01 Jan 1958 - 
- Vol. 20, Iss: 1, pp 102-107
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This article is published in Journal of the royal statistical society series b-methodological.The article was published on 1958-01-01. It has received 862 citations till now. The article focuses on the topics: Bayes' theorem & Fiducial marker.

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A generalization of bayesian inference

TL;DR: Procedures of statistical inference are described which generalize Bayesian inference in specific ways Probability is used in such a way that in general only bounds may be placed on the probabilities of given events, and probability systems of this kind are suggested both for sample information and for prior information as discussed by the authors.

A Generalization of Bayesian Inference.

TL;DR: Procedures of statistical inference are described which generalize Bayesian inference in specific ways and some comments are made on the general class of models which produce upper and lower probabilities, and on the specific models which underlie the suggested inference procedures.
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The Selection of Prior Distributions by Formal Rules

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Comparing different supervised machine learning algorithms for disease prediction

TL;DR: It is found that the Support Vector Machine (SVM) algorithm is applied most frequently (in 29 studies) followed by the Naïve Bayes algorithm (in 23 studies), however, the Random Forest algorithm showed superior accuracy comparatively.
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Lindley distribution and its application

TL;DR: A treatment of the mathematical properties is provided for the Lindley distribution, which includes moments, cumulants, characteristic function, failure rate function, mean residual life function, and mean deviations.
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