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A weighted total-variation bound from relative entropy

Statement

Assume AC. Let μ,ν be Borel probability measures on Rd, and let W:Rd→[1,∞) be Borel measurable with ∫W2 dμ+∫W2 dν<∞. Then ∥μ−ν∥W≤2(∫W2 dμ+∫W2 dν)D(μ∥ν), where μ,ν are probability measures in the sense of Probability measures and probability spaces, ∥⋅∥W is defined in Weighted total variation for probability measures and D(μ∥ν) is the directional relative entropy of Kullback–Leibler divergence. If D(μ∥ν)=+∞, the inequality is understood in the extended-real sense and is immediate.

Facts & Assumptions

Given: AC; probability measures μ,ν; a Borel weight W≥1 with finite second moments under both measures.

[A1]

AC supplies the Radon–Nikodym representative used in the definition of directional relative entropy. The Axiom of Choice The Radon-Nikodym derivative as an almost-everywhere equivalence class

[F1]

If D(μ∥ν)<∞, then μ≪ν, the density r=dμ/dν is nonnegative, and D(μ∥ν)=∫(rlog⁡r) dν with 0log⁡0=0. Kullback–Leibler divergence Integrating against a Radon-Nikodym derivative recovers integration against the measure

[F2]

The directional relative entropy has finite negative part and ∫r dν=1. Kullback–Leibler divergence Integrating against a Radon-Nikodym derivative recovers integration against the measure

[F3]

Cauchy–Schwarz gives ∫∣fg∣ dν≤(∫∣f∣2dν)1/2(∫∣g∣2dν)1/2 for square-integrable f,g. Cauchy-Schwarz inequality for L2

[F6]

Integrals of integrable real functions are linear. The Lebesgue integral is linear on L1(μ)

Proof

Given: The hypotheses in the Statement.

1.1F4F5algebra

Define ϕ(0)=1 and ϕ(t)=tlog⁡t−t+1 for t>0. For 0<t≤1, the function h(t)=t−1−log⁡t satisfies h(1)=0 and h′(t)=1−1/t≤0. The mean value theorem on [t,1] gives h(t)≥0, so log⁡t≤t−1. Now k(t)=ϕ(t)−(1−t)2/2 satisfies k(1)=0 and k′(t)=log⁡t+1−t≤0 by [F4]–[F5]; another application of the mean value theorem gives k(t)≥0. At t=0 the inequality holds because 1≥1/2.

2.1F4F5step 1.1algebra

For t≥1, put g(t)=2(1+t)ϕ(t)−(t−1)2. By [F5], g(1)=g′(1)=0 and g′′(t)=4log⁡t+2/t≥0 using [F4] and log⁡t≥0 for t≥1. The mean value theorem applied first to g′ and then to g shows g′(t)≥0 and g(t)≥0 for t≥1. Combining with step 1.1 gives ∣1−t∣2≤2(1+t)ϕ(t)(t≥0).

3.1A1F1F2F3F6step 2.1given∎

It remains to consider finite D(μ∥ν). Let r=dμ/dν as in [F1]. For every Borel f with ∣f∣≤W, the Radon–Nikodym identity gives ∣∫f dμ−∫f dν∣≤∫W∣r−1∣ dν. Applying step 2.1 pointwise and [F3] with factors W1+r and 2ϕ(r) bounds this by ∫W2(1+r) dν2∫ϕ(r) dν=(∫W2dν+∫W2dμ)2D(μ∥ν). The moment hypotheses make the first factor finite, and [F1], [F2], and [F6] identify the second integral with the directional relative entropy, using ∫r dν=∫1 dν=1. Taking the supremum over f proves the claim.

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