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Hauptverfasser: Vákár, Matthijs, Ong, Luke
Format: Preprint
Veröffentlicht: 2018
Schlagworte:
Online-Zugang:https://arxiv.org/abs/1810.01837
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author Vákár, Matthijs
Ong, Luke
author_facet Vákár, Matthijs
Ong, Luke
contents In this note, we develop some of the basic theory of s-finite (measures and) kernels, a little-studied class that Staton has recently argued convincingly to be precisely the semantic counterpart of (first-order) probabilistic programs. We discuss their Carathéodory extension and extend Staton's analysis of their product measures. We give various characterisations of such kernels and discuss their relationship to the more commonly studied classes of $σ$-finite, subprobability and probability kernels. We use these characterisations to establish suitable Radon-Nikodým, Lebesgue decomposition and disintegration theorems for s-finite kernels. We discuss s-finite analogues of the classical randomisation lemma for probability kernels. Throughout, we give some examples to explain the connection with (first-order) probabilistic programming. Finally, we briefly explore how some of these results extend to quasi-Borel spaces, and hence how they apply to higher-order probabilistic programming.
format Preprint
id arxiv_https___arxiv_org_abs_1810_01837
institution arXiv
publishDate 2018
record_format arxiv
spellingShingle On S-Finite Measures and Kernels
Vákár, Matthijs
Ong, Luke
Probability
In this note, we develop some of the basic theory of s-finite (measures and) kernels, a little-studied class that Staton has recently argued convincingly to be precisely the semantic counterpart of (first-order) probabilistic programs. We discuss their Carathéodory extension and extend Staton's analysis of their product measures. We give various characterisations of such kernels and discuss their relationship to the more commonly studied classes of $σ$-finite, subprobability and probability kernels. We use these characterisations to establish suitable Radon-Nikodým, Lebesgue decomposition and disintegration theorems for s-finite kernels. We discuss s-finite analogues of the classical randomisation lemma for probability kernels. Throughout, we give some examples to explain the connection with (first-order) probabilistic programming. Finally, we briefly explore how some of these results extend to quasi-Borel spaces, and hence how they apply to higher-order probabilistic programming.
title On S-Finite Measures and Kernels
topic Probability
url https://arxiv.org/abs/1810.01837