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Shorter versus longer-duration antibiotic treatments for immunocompetent patients with bloodstream infections: a Bayesian perspective. [PDF]
EClinicalMedicineAkhmedullin R, Gaipov A.
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Synthese, 2009
Bayesian decision theory is here construed as explicating a particular concept of rational choice and Bayesian probability is taken to be the concept of probability used in that theory. Bayesian probability is usually identified with the agent’s degrees of belief but that interpretation makes Bayesian decision theory a poor explication of the relevant ...
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Bayesian decision theory is here construed as explicating a particular concept of rational choice and Bayesian probability is taken to be the concept of probability used in that theory. Bayesian probability is usually identified with the agent’s degrees of belief but that interpretation makes Bayesian decision theory a poor explication of the relevant ...
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Epistemic uncertainty in Bayesian predictive probabilities
Journal of Biopharmaceutical Statistics, 2023Bayesian predictive probabilities have become a ubiquitous tool for design and monitoring of clinical trials. The typical procedure is to average predictive probabilities over the prior or posterior distributions. In this paper, we highlight the limitations of relying solely on averaging, and propose the reporting of intervals or quantiles for the ...
Charles C. Liu, Ron Xiaolong Yu
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A RECURSION FORMULA FOR BAYESIAN PROBABILITIES
Psychological Reports, 2003A recursion formula for Bayes' formula is derived. The formula is useful in applications in which diagnoses are added in a stepwise way to predict a criterion. On each step, changes in various diagnostic measures can be easily evaluated.
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2014
From the basics to the forefront of modern research, this book presents all aspects of probability theory, statistics and data analysis from a Bayesian perspective for physicists and engineers. The book presents the roots, applications and numerical implementation of probability theory, and covers advanced topics such as maximum entropy distributions ...
Linden, W., Dose, V., Toussaint, U.
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From the basics to the forefront of modern research, this book presents all aspects of probability theory, statistics and data analysis from a Bayesian perspective for physicists and engineers. The book presents the roots, applications and numerical implementation of probability theory, and covers advanced topics such as maximum entropy distributions ...
Linden, W., Dose, V., Toussaint, U.
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A Bayesian probability network
AIP Conference Proceedings, 1986A model of an associative neural network is developed in which the state of each node is described by a probability density. The realization of the network is based on the pairwise joint probabilities obtained from a training set of states. A positive definite ‘‘energy’’ functional of the probabilities may be constructed from Bayes’ rule of statistical
C. H. Anderson, E. Abrahams
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Bayesian Probability Boxes in Risk Assessment
Journal of Statistical Theory and Practice, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Montgomery, Victoria J. +2 more
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