TheoremBase

Disintegration of a Probability Measure on a Product with a Polish Factor: Existence and Almost-Everywhere Uniqueness of the Conditional Kernel

A probability measure on the product of a measurable space and a complete separable metric space is the composite of its first marginal with a probability kernel, and this kernel is unique up to a null set of the marginal.

Statement

In the setting of Measure Spaces and the Lebesgue Integral: Standing Notation, let (Y,Y)(Y,\mathcal{Y}) be a measurable space, let (Z,d)(Z,d) be a complete and separable metric space with Borel σ\sigma-algebra B(Z)\mathcal{B}(Z), and let π\pi be a measure on the product σ\sigma-algebra Y⊗B(Z)\mathcal{Y}\otimes\mathcal{B}(Z) with π(Y×Z)=1\pi(Y\times Z)=1. Let μ\mu be its first marginal, μ(A)=π(A×Z)\mu(A)=\pi(A\times Z) for A∈YA\in\mathcal{Y}; it is the image measure of π\pi under the projection (y,z)↦y(y,z)\mapsto y, which is measurable with respect to Y⊗B(Z)\mathcal{Y}\otimes\mathcal{B}(Z) and Y\mathcal{Y} by claim 5 of Sections of Product-Measurable Sets and Maps Are Measurable, and Insertion Maps into Products Are Measurable, hence a probability measure on (Y,Y)(Y,\mathcal{Y}) by claim 1 of Image Measures, Measures with Densities, and Change of Variables. For a probability kernel κ\kappa from (Y,Y)(Y,\mathcal{Y}) to (Z,B(Z))(Z,\mathcal{B}(Z)) we write κy=κ(y,⋅)\kappa_{y}=\kappa(y,\cdot), and μ⊗κ\mu\otimes\kappa is the composite measure of Integration Against a Probability Kernel: Measurable Sections, the Composite Measure on the Product and the Iterated Integral §composite.

1. (Existence) There is a probability kernel κ\kappa from (Y,Y)(Y,\mathcal{Y}) to (Z,B(Z))(Z,\mathcal{B}(Z)) with π=μ⊗κ\pi=\mu\otimes\kappa; by Integration Against a Probability Kernel: Measurable Sections, the Composite Measure on the Product and the Iterated Integral §composite and Integration Against a Probability Kernel: Measurable Sections, the Composite Measure on the Product and the Iterated Integral §rectangles this means

π(A×B)=∫Y1A(y) κ(y,B) μ(dy)(A∈Y, B∈B(Z)).\pi(A\times B)=\int_{Y}\mathbf{1}_{A}(y)\,\kappa(y,B)\,\mu(dy)\qquad(A\in\mathcal{Y},\ B\in\mathcal{B}(Z)).

2. (Uniqueness) If κ\kappa and κ′\kappa' are probability kernels from (Y,Y)(Y,\mathcal{Y}) to (Z,B(Z))(Z,\mathcal{B}(Z)) with π=μ⊗κ=μ⊗κ′\pi=\mu\otimes\kappa=\mu\otimes\kappa', then the set of the y∈Yy\in Y with κy≠κy′\kappa_{y}\ne\kappa'_{y} belongs to Y\mathcal{Y} and has μ\mu-measure 00.

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