Abstract
There is a formula that yields the invariant measure of a form-invariant model \(p(x|\xi )\) in a straightforward way without analysis of the symmetry group, in particular without knowledge of the multiplication function. This is useful because the analysis of the symmetry group may be difficult. This is even of basic importance, because the formula allows one to generalise the definition of the prior \(\mu \) to cases where form invariance does not exist or is not known to exist. Thus we do not require form invariance for the application of Bayes’ theorem.
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Harney, H.L. (2016). Going Beyond Form Invariance: The Geometric Prior. In: Bayesian Inference. Springer, Cham. https://doi.org/10.1007/978-3-319-41644-1_9
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DOI: https://doi.org/10.1007/978-3-319-41644-1_9
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