How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Dependent-input Shapley effects are nonnegative and sum to one
Statement
Assume AC and the positive-variance hypotheses of Shapley effects for dependent inputs. Then is monotone with , , and for every . Every , and Moreover, on the exact-oracle input for this game, the procedure Exact finite-permutation Shapley effects terminates after at most coalition-value calls and returns the Shapley effects defined above.
Facts & Assumptions
Given: AC, , , and the variance game and effects from the definition.
The Axiom of Choice: AC is assumed for the conditional-expectation supplier.
Conditional expectation is the l2 orthogonal projection: under AC, conditional expectation is the orthogonal projection onto the corresponding subspace and fixes measurable inputs.
Shapley effects for dependent inputs: and is the average normalized marginal contribution over all permutations.
Exact finite-permutation Shapley effects: the procedure initializes the accumulators, starts each permutation with , adds at entry , updates to , and returns the accumulated values divided by .
Proof
Given: The objects in the Statement and facts [A1], [F1]–[F3].
Fix , and write and . The subspaces of - and -measurable functions are nested. For every in the smaller subspace, because also belongs to the larger subspace. Thus and have the same orthogonal projection onto the smaller subspace, namely , so . Pythagoras gives .
For any permutation , sum the successive increments in the order of that permutation. Every intermediate coalition value appears once positively and once negatively, leaving . The projection in [F1] fixes , so ; the empty-set projection is constant , so . Step 1.1 gives monotonicity, so these endpoint values imply for every coalition. Thus the increments sum to .
Each increment in step 2.1 is nonnegative by step 1.1. Average over the finite set of permutations and divide by . The resulting effects are nonnegative and their sum is .
In the procedure [F3], before each entry of a permutation , the current set is exactly : it starts empty and each preceding entry is added once. Thus the increment added to is . There are permutations with entries each, so the loops perform finitely many iterations and at most exact coalition-value calls; every queried value is available by the stated oracle input. Summing the increments gives , and division by returns exactly by [F2].
Depends on
Used by
Dependency tree · two levels
12 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Eunhye Song, Barry L. Nelson, and Jeremy Staum, Shapley Effects for Global Sensitivity Analysis: Theory and Computation, §3.1 (standard reference, not scraped)