On S-Finite Measures and Kernels

Abstract

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 Carath\'eodory 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 $\sigma$-finite, subprobability and probability kernels. We use these characterisations to establish suitable Radon-Nikod\'ym, 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.