Contextual Equivalence for a Probabilistic Language with Continuous Random Variables

We present a complete reasoning principle for contextual equivalence in an untyped probabilistic programming language. The language includes continuous random variables, conditionals, and scoring. The language also includes recursion, since in an untyped language the standard call-by-value fixpoint combinator is expressible. The language is similar to that of Borgström et al. [5]. To demonstrate the usability of our characterization, we use it to prove that reordering the draws in a probabilistic program preserves contextual equivalence. This allows us to show, for example, that (letx = e1 in let y = e2 in e0) =ctx (let y = e2 in letx = e1 in e0) (provided x is not among the free variables of e2 and y is not among the free variables of e1) despite the fact that e1 and e2 may have the effect of drawing from the source of entropy.