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Lookup NU author(s): Dr Pier Giovanni Bissiri
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© 2019 Elsevier B.V. Bissiri et al. (2016) propose a framework for general Bayesian inference using loss functions which connect parameters with data, and the updated posterior distribution is characterized through a set of axioms. The result, which is restricted to finite probability spaces, is extended in this paper to spaces which are subsets of the real line.
Author(s): Bissiri PG, Walker SG
Publication type: Article
Publication status: Published
Journal: Statistics and Probability Letters
Year: 2019
Volume: 152
Pages: 89-91
Print publication date: 01/09/2019
Online publication date: 08/05/2019
Acceptance date: 12/04/2019
ISSN (print): 0167-7152
Publisher: Elsevier BV * North-Holland
URL: https://doi.org/10.1016/j.spl.2019.04.005
DOI: 10.1016/j.spl.2019.04.005
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