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Likelihood-ratio vector for a point-mass model

Example

Assume AC. Let X=N≥1 with its discrete σ-field, Pk=δk, and Q=∑k≥12−kPk. The vector statistic T(j)=(dPk/dQ(j))k≥1 is minimal sufficient and injective.

Facts & Assumptions

Given: AC, the point-mass family, and the positive geometric weights.

[A1]

The Axiom of Choice: AC is the axiom branch of the likelihood-ratio-vector theorem.

[F1]

A countable mixture likelihood-ratio vector is minimal sufficient: the RN-density vector relative to a positive countable mixture is minimal sufficient.

[F2]

Minimal sufficient statistics: minimality is interpreted modulo common model-null sets.

Proof

1.1A1F1givenalgebra

Since Q({j})=2−j and Pk({j})=1 exactly when j=k, the density is fk(j)=2k1{j=k}. Therefore T(j) has coordinate j equal to 2j and all other coordinates zero.

2.1A1F1F2step 1.1givenalgebra∎

The discrete metric on N≥1 is complete and separable, and its Borel sigma-field is the full sigma-field. The weights 2−k>0 sum to one, and step 1.1 gives finite nonnegative measurable density versions. Since every Q-atom has positive mass, the common Q-null set on which these versions are reset is empty. Thus all hypotheses of [F1], including AC [A1], hold, and that theorem proves minimal sufficiency. The vectors in step 1.1 are distinct for distinct j, proving injectivity. Finally, a set null under every Pj contains no j, so the family-null ideal is trivial and the minimality comparison in [F2] is exact in this model.

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