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Conditional-independence splice lemma
Statement
Assume Choice. Let on and on be probability measures with the same marginal, where all three spaces are standard Borel. There is a unique probability measure on whose and marginals are and and under which the first and third coordinates are conditionally independent given the second.
Facts & Assumptions
Given: Choice, the three standard-Borel spaces and the compatible laws in the statement. Denote their common marginal by .
A regular conditional distribution exists for a standard-Borel target. (Existence of regular conditional distributions for standard borel targets)
Such a conditional kernel given a standard-Borel random element factors through that element as an everywhere probability kernel. (Regular conditional kernels factor through a standard borel conditioning variable)
Integrating a nonnegative product-measurable function against a finite kernel produces a measurable function of the source variable. (Measurability of integration against a kernel)
Monotone convergence applies to nonnegative measurable integrands. (Monotone convergence for the integral)
Conditional independence is equivalent to invariance of the conditional law of one side when the other side is adjoined to the conditioning sigma-algebra. (Conditional-independence equivalences and preservation)
Equality of two probability measures on a generating pi-system extends to the generated sigma-algebra. (Dynkin's pi-lambda theorem)
Sections of product-measurable functions, in particular indicators of product-measurable sets, are measurable. (Every section of a product-measurable function is measurable)
Proof
Apply [F1] to the coordinate pair on [F1, F2] and then [F2]. This gives a probability kernel such that, for measurable, Choice is used precisely by [F1]--[F2] to select and factor the conditional law.
Lift to the kernel [F3, F4, F7, step 1.1] and, for a measurable , set Each section is measurable by [F7], and the integrand is measurable by [F3], applied to and . For disjoint , their sections are disjoint and [F4] passes the increasing partial sums through the outer integral. Thus is countably additive; and . Hence it is a probability measure, including when one of the displayed test sets below is empty.
Taking in step 2.1 gives [F6, step 1.1, step 2.1] . Taking and using step 1.1 gives . The rectangle pi-systems and [F6] therefore identify both required marginals on their full product sigma-algebras.
For bounded measurable , write [F3, F5, step 1.1, step 2.1, step 3.1] . The construction in step 2.1, first for indicators, then for simple functions, and then for positive and negative parts, shows The marginal and step 1.1 likewise show . Criterion [F5] now gives .
Let be any other law with the two marginals and the stated [F5, F6, step 2.1, step 3.1] conditional independence. Its marginal makes a conditional expectation of given ; [F5] then makes it the conditional expectation given . Consequently, for every measurable rectangle, which equals the value of from step 2.1. Rectangles form a pi-system containing the whole space, so [F6] gives .
Depends on
- The Axiom of Choice
- Conditional-independence equivalences and preservation
- Existence of regular conditional distributions for standard borel targets
- Regular conditional kernels factor through a standard borel conditioning variable
- Measurability of integration against a kernel
- Every section of a product-measurable function is measurable
- Monotone convergence for the integral
- Dynkin's pi-lambda theorem
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
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Sources
- Aldous-Chewi probability notes, Lecture 9 (standard reference, not scraped)