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Bayesian Nets and CausalityPhilosophical and Computational Foundations$
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Jon Williamson

Print publication date: 2004

Print ISBN-13: 9780198530794

Published to Oxford Scholarship Online: September 2007

DOI: 10.1093/acprof:oso/9780198530794.001.0001

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OBJECTIVE BAYESIANISM

OBJECTIVE BAYESIANISM

Chapter:
(p.65) 5 OBJECTIVE BAYESIANISM
Source:
Bayesian Nets and Causality
Author(s):

Jon Williamson (Contributor Webpage)

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198530794.003.0005

Objective Bayesianism imposes two norms on degrees of belief: degrees of belief should be constrained by empirical information and they should otherwise be as equivocal as possible. The origins of objective Bayesianism are explained, with the work of Jakob Bernoulli and Laplace presented at some length. A contemporary reading of the two norms is developed in detail. Then, it is shown how Bayesian nets can be used to represent objective Bayesian degrees of belief (this leads to what are now called objective Bayesian nets).

Keywords:   calibration, Jakob Bernoulli, Laplace, entropy, maximum entropy principle, objective Bayesian net

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