Abstract
In Sect. 2.1, Bayes’ theorem is derived. The prior distribution that it contains, must be defined so that it transforms as a density. Transformations of densities and functions are discussed in Sect. 2.2. A symmetry argument can define the prior. This is described in Sects. 2.3 and 2.4. Prior distributions are not necessarily proper. In Sect. 2.5, we comment on improper distributions because it is unusual to admit any of them.
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© 2003 Springer-Verlag Berlin Heidelberg
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Harney, H.L. (2003). Bayes’ Theorem. In: Bayesian Inference. Advanced Texts in Physics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-06006-3_2
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DOI: https://doi.org/10.1007/978-3-662-06006-3_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05577-5
Online ISBN: 978-3-662-06006-3
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