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Additivity of KL divergence for finite product laws

Statement

Assume AC. Let n∈N with n≥1. For each i<n, let (Xi,Ai) be a measurable space and let Pi,Qi be probability measures on it. On the finite product measurable space set P=⨂i<nPi,Q=⨂i<nQi. With the KL convention of Kullback–Leibler divergence, D(P∥Q)=∑i<nD(Pi∥Qi), where a sum with an infinite term is +∞.

Facts & Assumptions

Given: AC, a natural number n≥1, measurable spaces (Xi,Ai) for i<n, probability laws Pi,Qi, and their finite product measures P,Q.

[A1]

The Axiom of Choice: AC is assumed by the Radon–Nikodym suppliers in the KL definition.

[F1]

Kullback–Leibler divergence and The Radon-Nikodym derivative as an almost-everywhere equivalence class: if Pi≪Qi, its density is an almost-everywhere class ri satisfying Pi(A)=∫Ari dQi, and D(Pi∥Qi)=∫log⁡ri dPi; the negative part is finite.

[F2]

The product sigma-algebra and its finite iterates and The product measure of two sigma-finite measure spaces: finite products use the iterated product sigma-algebra and product measures whose rectangle values are the products of factor measures.

[F4]

The measure with density f relative to μ and The indefinite integral of a nonnegative measurable function is a measure: a nonnegative measurable density r defines the measure r dQ by (r dQ)(E)=∫Er dQ.

[F5]

Tonelli's theorem for nonnegative measurable functions on a sigma-finite product and Fubini's theorem for L^1 functions on a sigma-finite product: nonnegative product integrals factor by Tonelli, and integrable product functions may be integrated sectionwise by Fubini.

[F6]

Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm: for positive x1,…,xn, log⁡(∏ixi)=∑ilog⁡xi.

Proof

1.1A1F2F3given

If Pi≪̸Qi for some i<n, choose Ai∈Ai with Qi(Ai)=0<Pi(Ai). Let E=∏j<nEj, where Ei=Ai and Ej=Xj for j≠i. The product rectangle has Q(E)=0 and P(E)=Pi(Ai)>0 by [F2, F3]. Hence P≪̸Q, so the left side is +∞; the corresponding term on the right is also +∞ and the equality holds.

1.2A1F1F2F3F5given

Now suppose Pi≪Qi for every i<n, and choose nonnegative representatives ri=dPi/dQi. Define r(x0,…,xn−1)=∏i<nri(xi). Each coordinate function x↦ri(xi) is measurable by the finite product sigma-algebra definition: its level-set preimages are measurable rectangles. Hence the vector of coordinate values is measurable, since rectangles generate the Borel sigma-algebra of Rn; composing with the continuous multiplication map gives measurable r. Repeated Tonelli and the rectangle formulas give ∫Er dQ=∏i<n∫Airi dQi=∏i<nPi(Ai)=P(E) for every measurable rectangle E=∏i<nAi; applying the same calculation to the full space gives ∫r dQ=1.

2.1A1F3F4step 1.2

The measure r dQ is a probability measure by [F4] and step 1.2. The product rectangles form a generating pi-system and the finite product spaces are sigma-finite, so [F3] and the rectangle identity in step 1.2 imply r dQ=P on the entire product sigma-algebra. Therefore r=dP/dQ as a Radon–Nikodym class.

3.1A1F1F5F6step 2.1algebra∎

Each ri is finite Qi-almost everywhere because ∫ri dQi=1, and Pi({ri=0})=∫{ri=0}ri dQi=0; thus 0<ri<∞ Pi-almost everywhere. Therefore [F6] gives log⁡r=∑i<nlog⁡ri(xi) P-almost everywhere. Each log⁡ri has integrable negative part by [F1], and the negative part of their finite sum is bounded by the sum of those negative parts. Split each summand into positive and negative parts: Tonelli factors each nonnegative part through the product law, and Fubini applies to the negative parts, which are integrable. Hence, allowing +∞ for positive parts, ∫log⁡r dP=∑i<n∫log⁡ri dPi=∑i<nD(Pi∥Qi). By [F1] and step 2.1 the left side is D(P∥Q), proving the claim.

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