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The sum of exponential-family statistics is sufficient for an IID sample

Statement

Assume AC. Let (Y,Y) be standard Borel, let μ be a sigma-finite measure, and let (Pη)η∈Ω be a nonempty exponential family of Exponential families and full rank with density pη(y)=h(y)exp⁡{ηTT(y)−A(η)}. For each finite n≥1, the IID sample law Pη⊗n has density ∏i=1nh(yi)exp⁡ ⁣{ηT∑i=1nT(yi)−nA(η)} relative to μ⊗n, and Tn(y1,…,yn)=∑i=1nT(yi) is sufficient for the sample. No full-rank, completeness, or converse characterization is asserted.

Facts & Assumptions

Given: AC, the standard-Borel sample space, sigma-finite μ, and a nonempty family with the displayed exponential-family density.

[A1]

The Axiom of Choice is assumed by the common-reference factorization criterion and its conditional-law suppliers. The Axiom of Choice.

[F1]

An exponential-family density is pη=hexp⁡{ηTT−A(η)} and integrates to one against μ. Exponential families and full rank.

[F2]

Finite product sigma-algebras are generated by measurable rectangles, and finite products of sigma-finite measures are sigma-finite and satisfy the rectangle formula. The product sigma-algebra and its finite iterates For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique.

[F3]

Tonelli integrates nonnegative product densities by iterated integrals. Tonelli's theorem for nonnegative measurable functions on a sigma-finite product.

[F4]

A nonnegative measurable density induces a measure by integration. The indefinite integral of a nonnegative measurable function is a measure.

[F5]

Measures agreeing on a generating pi-system with a finite exhaustion agree on the product sigma-algebra. Measures agreeing on a generating pi-system are equal under an increasing finite-measure exhaustion from that pi-system.

[F6]

The finite sample product of standard-Borel spaces is standard Borel, including the empty-product singleton; for k≥1, the Euclidean statistic space Rk with its Borel sigma-algebra is standard Borel. Finite products of standard Borel spaces are standard Borel Finite-dimensional Euclidean space with its Borel sigma-algebra is standard Borel.

[F7]

If every likelihood ratio relative to one in-model reference law is a Borel function of a statistic, the statistic is sufficient on standard-Borel spaces. Common-reference factorization criterion for sufficiency.

[F8]

Sufficiency means there is one conditional-law kernel of the data given the statistic that works for every parameter. Sufficient statistics.

[F9]

Finite-valued measurable functions are closed under finite sums and products. The closure proposition supplies sums, and the arithmetic theorem supplies products. Closure properties of measurable functions used by the integral Arithmetic and lattice operations preserve measurability whenever they are defined.

Proof

Given: The hypotheses in the Statement.

1.1F1F2F3F4F5F9given

For fixed η, each coordinate pullback of pη is measurable on the product sigma-algebra [F2], and the product density gη(y1:n)=∏ipη(yi) is measurable by [F9]. Its integral against μ⊗n is one by [F2], repeated Tonelli [F3], and ∫pη dμ=1. Thus gη dμ⊗n is a probability measure by [F4]. On every measurable rectangle it equals ∏iPη(Ai) by the rectangle formula and Tonelli, so the sigma-finite pi-system uniqueness theorem [F5] identifies it with the IID product law. Expanding gη gives the density displayed in the Statement.

2.1F1step 1.1algebrachoose

Since Ω is nonempty, choose η0∈Ω. The density ratio on the common support is gη(y1:n)gη0(y1:n)=exp⁡{(η−η0)TTn(y1:n)−n(A(η)−A(η0))}. If any h(yi)=0, both product densities vanish, so the same positive Borel function of Tn satisfies gη=rη(Tn)gη0 everywhere. Integrating this identity on each measurable set proves that it is a version of the Radon–Nikodym derivative under Pη0⊗n.

3.1A1F6F7F8step 2.1given∎

By [F6] the finite sample space is standard Borel. If k≥1, [F6] also gives that the statistic target Rk is standard Borel. If k=0, R0 is the empty product, a singleton with its full two-element sigma-algebra, which is standard Borel by the empty-product case of [F6]. In this case Tn is the unique constant map, the dot products in step 2.1 are empty sums equal to zero, and its likelihood-ratio expression is still a Borel function of this singleton statistic. Thus both target cases meet the standard-Borel hypothesis. The reference Pη0⊗n belongs to the family, and step 2.1 makes every likelihood ratio a Borel function of Tn. Applying [F7] gives a common conditional-law kernel, which is sufficiency by [F8]. The sole choice-axiom use is inherited from [A1] and [F7].

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