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BY arbitrary dependence and BH PRDS

1 · Prerequisites

2 · Summary

The Benjamini–Yekutieli (BY) step-up rule uses critical values kq/(mHm), where Hm=∑j=1m1/j. For any finite family of valid p-values, its FDR is at most (m0/m)q under arbitrary dependence. The proof sums each true-null rejection contribution over the possible rejection counts and applies only marginal superuniformity.

Ordinary Benjamini–Hochberg (BH) uses critical values kq/m; these equal the BY cutoffs when m=1 and are larger when m>1. Its separate guarantee here assumes that the p-value vector is positive regression dependent on the true-null coordinates (PRDS): conditional probabilities of all increasing Borel sets must have nondecreasing versions as each true-null p-value increases. Under that exact condition, BH also has FDR at most (m0/m)q. PRDS is a distributional condition; pairwise positive covariance alone does not verify it, and two-sided Gaussian tests have no blanket PRDS guarantee. See the companion examples for a discrete independent threshold comparison and a counterexample to the pairwise-correlation shortcut.

3 · Logical flowchart

4 · Definitions, theorems and proofs

AlgorithmAlgorithm: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

Benjamini–Yekutieli step-up procedure

Definition

Input an integer m≥1, observed values p1,…,pm∈[0,1] of p-value statistics (Valid p-values), and a target level q∈(0,1). Let Hm=∑j=1m1/j be the harmonic number from Harmonic numbers for set-cover analysis. For k=1,…,m, set

ck:=kqmHm.

Order the pairs (pi,i) lexicographically, so equal values are ordered by their original indices, and write the ordered values p(1)≤⋯≤p(m). Set

R:=max⁡({k∈{1,…,m}:p(k)≤ck}∪{0}).

Reject exactly the hypotheses at ranks 1,…,R; when R=0, reject none. Because Hm≥1, each critical value satisfies 0<ck≤q/Hm≤q<1. This definition specifies the procedure; no FDR guarantee is asserted here.

LemmaStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

The unit interval with its Borel structure is standard Borel

Statement

Let I=[0,1] with the subspace topology from the usual real topology and with its Borel sigma-algebra. Then (I,B(I)) is a standard-Borel space (Standard Borel spaces).

Facts & Assumptions

Given: The usual real metric d(x,y)=∣x−y∣ and the subspace I=[0,1].

[F2]

The reals are complete: every Cauchy sequence in the usual real metric converges in R.

[F3]

Q is countably infinite: Q is countably infinite, so there is a bijection from Q to N.

[F4]

The rationals embed densely in the reals: between any two distinct real numbers lies a rational.

[F5]

Every subset of an at most countable set is at most countable: every subset of an at most countable set is at most countable; countable means finite or bijective with N (Finite, countably infinite, countable, uncountable, Equinumerous sets, A≈B and A⪯B).

[F7]

The Borel sigma-algebra of a topological space: the Borel sigma-algebra is generated by open sets and is closed under complements.

[F9]

Polish spaces are separable completely metrizable spaces: a space is Polish if it is separable and has a compatible complete metric; Standard Borel spaces identifies a measurable space with the Borel structure of a Polish presentation.

[A1]

The closed interval I=[0,1] is {x∈R:0≤x≤1} (Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[A3]

The metric on I is the restriction dI=d∣I×I (Isometry, isometric embedding, and the subspace metric on a subset).

Proof

technique · direct

Given: I=[0,1] with the usual subspace topology and Borel sigma-algebra.

1.1F1F6F7F10A1algebra

The interval is closed in R: for z∉I, [F6] and [A1] give either z<0 or z>1. If z<0, set r=−z>0; then every y∈B(z,r) satisfies y<z+r=0. If z>1, set r=z−1>0; then every y∈B(z,r) satisfies y>z−r=1. By [F1] these are open neighborhoods disjoint from I, so its complement is open by [F10]. Thus I is Borel by [F7].

1.2F3F4F5F6A1givenchoose

The set D:=Q∩I is at most countable: restrict the bijection Q→N from [F3] to D, then apply [F5]. It is dense in I. Indeed, for x∈I and ε>0, if x=1 choose q=1. If x<1, then x+ε>x; take b=x+ε when x+ε≤1, and b=1 otherwise. In either case b>x and b−x≤ε, with strict inequality in the second case. By [F4] choose a rational q with x<q<b; then q∈D and ∣q−x∣<ε. The order comparisons use [F6] and the interval endpoints use [A1].

2.1A2A3F2step 1.1given

Let (xn) be a Cauchy sequence in I under dI. By [A2]–[A3], Cauchy distances are the same in I and R, so [F2] gives a real limit x. If x∉I, step 1.1 gives an open ball about x disjoint from I, while convergence puts all sufficiently late xn in that ball, a contradiction. Hence x∈I and the sequence converges in the restricted metric; (I,dI) is complete.

3.1A2F8F9step 1.2step 2.1algebra∎

By steps 1.2 and 2.1, I is separable and completely metrizable, hence Polish by [F9]. Its Borel sigma-algebra is the trace of B(R) by [F8] and [A2]. The identity map from (I,B(R)∣I) to the Polish subspace I is therefore a bimeasurable bijection; [F9] makes (I,B(I)) standard Borel. This proves the claim without any choice axiom.

LemmaStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Leave-one-coordinate rejection partition for a step-up rule

Statement

Let m≥1, p=(p1,…,pm)∈[0,1]m, and critical values 0<c1≤⋯≤cm≤1. Give [0,1]m its finite product of the trace Borel sigma-algebras on [0,1]. Define the step-up rule by

R:=max⁡({k∈{1,…,m}:p(k)≤ck}∪{0}),

rejecting exactly ranks 1,…,R. Fix i∈{1,…,m}. Give the remaining-coordinate space [0,1]m−1 its finite product of the trace Borel sigma-algebras, with the empty product on the singleton empty tuple when m=1. Write the remaining values in increasing order as y(1)≤⋯≤y(m−1), and set y(0)=0. For 1≤k≤m, let

Ci,k:={y(k−1)≤ck}∩⋂r=km−1{y(r)>cr+1},

with an empty intersection interpreted as the whole remaining-coordinate space. Put Di,k:=⋃j=1kCi,j. For x∈[0,1]m, let Ii(x)=1 if the rule rejects coordinate i, and Ii(x)=0 otherwise. Then:

  1. For every k, the following identity of subsets of [0,1]m holds: {x∈[0,1]m:Ii(x)=1, R(x)=k}={x∈[0,1]m:xi≤ck}∩{x∈[0,1]m:x−i∈Ci,k}. In particular, every input in the right-hand side has exactly k rejections and rejects i.
  2. The sets Ci,1,…,Ci,m are a disjoint Borel partition of [0,1]m−1.
  3. For k<m, Di,k=⋂r=km−1{y(r)>cr+1}, and Di,m is the whole space. Each Di,k is a coordinatewise increasing Borel set.

For m=1, the remaining-coordinate space is the singleton empty tuple with its full sigma-algebra, and Ci,1=Di,1 is the whole space.

Facts & Assumptions

Given: m≥1, a p-value vector, nondecreasing critical values 0<c1≤⋯≤cm≤1, and the displayed step-up rule.

[F1]

The Borel sigma-algebra of a topological space: closed half-lines and finite unions and intersections of their inverse images are Borel.

[F2]

A measurable function between measurable spaces: a map is measurable when the preimage of each Borel set is measurable.

[F3]

The product sigma-algebra and its finite iterates: the finite product sigma-algebra is generated by measurable rectangles, so coordinate cylinders with Borel bases are measurable.

[F4]

Seven generating families for the Borel sigma-algebra on the real line: the closed left rays (−∞,t] generate B(R), since they are complements of the open right rays in the theorem's list.

Proof

1.1givenF1F2F3F4algebra

For 1≤r≤m−1 and t∈R, {y(r)≤t} is the finite union over r-element index sets J of ⋂j∈J{yj≤t}, since at least r remaining values are at most t exactly when the rth ordered value is at most t. Each coordinate cylinder is measurable in the stated finite product structure by [F1] and [F3], so these sublevel sets are Borel. Since the closed left rays generate B(R) by [F4], each order statistic is Borel by [F2]. The coordinate-deletion projection from [0,1]m to [0,1]m−1 is measurable: preimages of measurable rectangles are finite intersections of coordinate cylinders, and the rectangles generate the product sigma-algebra by [F3]. Thus lifting a Borel set in the remaining-coordinate space gives a Borel set in the full product. If y≤z coordinatewise, at least r coordinates of z are at most z(r); their corresponding coordinates of y are also at most z(r), so y(r)≤z(r). Every remaining-coordinate order statistic is therefore coordinatewise nondecreasing.

2.1givenstep 1.1algebra

Fix k and suppose pi≤ck. Rank k passes exactly when at least k−1 other coordinates are at most ck, which is y(k−1)≤ck; for k=1 this holds by y(0)=0. For each j>k, since pi≤ck≤cj, rank j passes exactly when at least j−1 other coordinates are at most cj, namely y(j−1)≤cj. Hence R=k exactly when the first condition of Ci,k holds and every higher rank fails, which is p−i∈Ci,k. If k=m, i is automatically among the first k ranks. If k<m and i is not among the first k ranks, then p(k+1)≤pi≤ck≤ck+1 would make rank k+1 pass. Conversely, if R=k and i is rejected, then pi≤p(k)≤ck, rank k passes and every higher rank fails, so the conditions defining Ci,k hold.

3.1givenstep 1.1step 2.1algebra

For any remaining vector y, replace coordinate i by 0. Since c1>0, rank one passes. Every rank occupied by a zero-valued coordinate also passes because all critical values are positive, so R includes all zero-valued coordinates and rejects the inserted coordinate i. Thus the resulting rejection count is some r∈{1,…,m}. By step 2.1, y∈Ci,r; hence the sets cover the space. If k<ℓ and y∈Ci,k, its condition at r=ℓ−1 gives y(ℓ−1)>cℓ, while membership in Ci,ℓ would give y(ℓ−1)≤cℓ. Thus the sets are disjoint. They are Borel by step 1.1 and their finite defining inequalities.

4.1givenstep 1.1step 2.1step 3.1algebra∎

If y∈Ci,j for some j≤k<m, the defining inequalities include y(r)>cr+1 for every r≥k, so Di,k is contained in the displayed intersection. Conversely, suppose those inequalities hold and set pi=0. Rank one passes, and by the zero-coordinate argument in step 3.1 the inserted coordinate i is rejected. No rank ℓ≥k+1 can pass: that would require y(ℓ−1)≤cℓ, contrary to the assumed condition at r=ℓ−1. Thus the rejection count is some j≤k, and step 2.1 puts y in Ci,j. This proves the formula; when k=m, step 3.1 gives Di,m equal to the whole space. The formula is a finite intersection of Borel order-statistic superlevel sets and is coordinatewise increasing by step 1.1.

Remarks

The result is choice-free. It applies to BH and BY after substituting their respective nondecreasing critical-value sequences.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

Positive regression dependence on true-null coordinates (PRDS)

Definition

Let (Ω,F,P) be a probability space, let m≥1, and let P=(P1,…,Pm):Ω→[0,1]m be a random vector whose coordinates are p-value statistics (Valid p-values). Fix a designated true-null index set I0⊆{1,…,m}. For i∈I0, write μi for the law of Pi under P and define its support relative to [0,1] by

supp⁡(μi):={x∈[0,1]:μi(U)>0 for every relatively open neighborhood U of x}.

Give each coordinate [0,1] its trace Borel sigma-algebra (The Borel sigma-algebra of a topological space) and give [0,1]m the finite product sigma-algebra (The product sigma-algebra and its finite iterates). In this definition, “Borel set” means a member of that product sigma-algebra; thus “increasing measurable set” means coordinatewise increasing in this stated structure. The unit-interval lemma proves that [0,1] with this trace Borel structure is standard Borel (The unit interval with its Borel structure is standard Borel). The finite-product result then makes [0,1]m with the specified product sigma-algebra a standard-Borel target (Standard Borel spaces, Finite products of standard Borel spaces are standard Borel); its finite-product proof uses only finite choice in ZF. Under the Axiom of Choice (The Axiom of Choice), this target has a regular conditional distribution given σ(Pi), and the conditional-law factorization result supplies a kernel Ki:[0,1]→[0,1]m representing the conditional law of P given Pi=x (Existence of regular conditional distributions for standard borel targets, Regular conditional kernels factor through a standard borel conditioning variable, Conditional law given a random element).

The law of P is positive regression dependent on the true-null coordinates (PRDS on I0) if, for each i∈I0, such a conditional-law version can be chosen so that for every coordinatewise increasing Borel set D, the function

x⟼Ki(x,D)

is nondecreasing on supp⁡(μi). If I0=∅, this condition is vacuous. The monotonicity condition is a full conditional-law requirement; pairwise correlations alone do not verify it.

Remarks

The regular conditional law is a chosen version. PRDS requires the monotonicity on the stated support, including support points where a conditional version is not determined by an atom of positive mass. The companion examples include a finite counterexample showing that valid p-values can have positive pairwise covariance without satisfying PRDS. The BY source's one-sided Gaussian sufficient conditions do not imply a general guarantee for two-sided Gaussian tests; the PRDS theorem below applies only after its exact conditional monotonicity premise is established.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

BY controls FDR under arbitrary dependence

Statement

Let E=((X,A),Θ,(Pθ)θ∈Θ) be a statistical experiment (Statistical experiments), let m≥1, and fix a finite family of null hypotheses H01,…,H0m. For each i, let pi be a p-value statistic valid for H0i in the sense of Null-valid p-values and familywise and false-discovery error rates. For θ∈Θ, put

I0(θ):={i∈{1,…,m}:θ∈H0i},m0(θ):=∣I0(θ)∣.

For every q∈(0,1), the BY procedure in Benjamini–Yekutieli step-up procedure satisfies

FDR⁡θ≤m0(θ)mq≤q.

No dependence condition on the joint law of the p-values is required.

Facts & Assumptions

Given: The experiment and fixed finite family in the Statement, q∈(0,1), and p-value validity under each corresponding null law.

[F1]

Null-valid p-values and familywise and false-discovery error rates: I0(θ) is the set of true-null indices, Vθ counts rejected true nulls, and FDR⁡θ=Eθ[Vθ/(R∨1)].

[F2]

Benjamini–Yekutieli step-up procedure: BY uses the critical values ck=kq/(mHm) and rejects exactly the first R ranks, where R is the largest passing rank.

[F3]

Leave-one-coordinate rejection partition for a step-up rule: for any nondecreasing step-up critical values, {Ii=1,R=k}={pi≤ck}∩{p−i∈Ci,k}, and the sets Ci,k partition the remaining-coordinate space.

[F4]

Valid p-values yield level tests for nonempty disjoint alternatives: for a valid p-value and a nonempty null hypothesis, Pθ(pi≤u)≤u for every parameter in that null and every u∈[0,1]. Here i∈I0(θ) means θ∈H0i, so the null H0i is nonempty and the supplier applies.

[F5]

The expectation of an indicator is the probability of the event: Eθ[1A]=Pθ(A) for every event A.

[F6]

Linearity, monotonicity, and the modulus bound for expectation: expectation is linear on finite sums of integrable random variables.

[F7]

Expectation of a nonnegative or integrable random variable: expectation is integration with respect to the specified probability law.

[A1]

Each p-value is superuniform under every parameter in its corresponding null hypothesis.

Proof

technique · finite rejection-count decomposition and summation by parts

Given: A fixed family of m≥1 null hypotheses, p-values valid for their respective nulls, and q∈(0,1).

1.1F1F5F6F7givenconstruct

Fix θ∈Θ and let Ii indicate that BY rejects hypothesis i. Pointwise, Vθ/(R∨1)=∑i∈I0(θ)∑k=1mk−11{Ii=1,R=k}: if R=0 both sides are zero, and if R>0 only k=R contributes, with weight 1/R for each rejected true null. This finite sum is bounded and integrable by [F7]; [F5] and [F6] therefore give FDR⁡θ=∑i∈I0(θ)∑k=1mk−1Pθ(Ii=1,R=k).

1.2F2F3F4givenalgebra

Fix i∈I0(θ) and put t=q/(mHm) and Jj=((j−1)t,jt] for j=1,…,m. Since θ∈H0i, that null is nonempty and [F4] at u=0 gives Pθ(pi=0)=0. Since BY has ck=kt, [F3] splits each event {Ii=1,R=k} into the disjoint events {pi∈Jj, p−i∈Ci,k} for j≤k, apart from that null zero event. Using 1/k≤1/j for k≥j and that the Ci,k partition the remaining coordinates, ∑k=1mk−1Pθ(Ii=1,R=k)=∑j=1m∑k=jmk−1Pθ(pi∈Jj, p−i∈Ci,k)≤∑j=1mj−1Pθ(pi∈Jj).

2.1F2F4step 1.2algebra

Set Fj=Pθ(pi≤jt) for j=0,…,m. Then F0=Pθ(pi=0)=0, Fj≤jt by [F4], and Pθ(pi∈Jj)=Fj−Fj−1. Finite summation by parts gives ∑j=1m(Fj−Fj−1)/j=Fm/m+∑j=1m−1Fj(1/j−1/(j+1))≤t+t∑j=1m−11/(j+1)=tHm=q/m. Here mt=q/Hm≤q<1, and Hm=∑j=1m1/j.

3.1F1step 1.1step 1.2step 2.1algebra∎

Combining steps 1.2 and 2.1 bounds each true-null contribution in step 1.1 by q/m. Summing over the m0(θ) true nulls gives FDR⁡θ≤(m0(θ)/m)q≤q; with no true nulls the outer sum is empty and FDR is zero. No dependence condition is used, and the CDF summation-by-parts argument covers discrete superuniform p-values.

Remarks

For general superuniform p-values, a single interval ((j−1)t,jt] can have probability greater than its width t. The proof therefore bounds the weighted sum of interval probabilities by summation by parts of the superuniform CDF; it does not assume each interval has mass at most t.

LemmaStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

A PRDS bound for each BH true-null contribution

Statement

Let P=(P1,…,Pm) be p-value random variables in a probability space, let m≥1, q∈(0,1), and fix an index i in a designated true-null set I0. Suppose Pi is valid under this law and the law of P is PRDS on I0 as defined in Positive regression dependence on true-null coordinates (PRDS). Apply BH at level q, and let Ii indicate that i is rejected and R be the total number rejected. Then

E ⁣[IiR∨1]≤qm.

Facts & Assumptions

Given: A finite vector of p-values, a fixed true-null set containing i, q∈(0,1), validity of Pi, and PRDS on that set. The PRDS conditional-law existence convention carries the Axiom of Choice as stated in Positive regression dependence on true-null coordinates (PRDS).

[F1]

Positive regression dependence on true-null coordinates (PRDS): for each i∈I0 and each increasing Borel D⊆[0,1]m, there is a regular conditional-law version Ki(x,D) that is nondecreasing on the support of Pi.

[F2]

Leave-one-coordinate rejection partition for a step-up rule: for ck=kq/m, the events {Ii=1,R=k} are {Pi≤ck}∩{P−i∈Ci,k}; the sets Ci,k partition the remaining-coordinate space, and Di,k:=⋃j≤kCi,j are increasing Borel sets with Di,m the whole space.

[F3]

Null-valid p-values and familywise and false-discovery error rates: validity means P(Pi≤u)≤u for every u∈[0,1] under the corresponding true-null law.

[F4]

Conditional law given a random element: if Ki is a conditional law of P given Pi, then for every Borel event D, P(Pi∈A,P∈D)=∫AKi(x,D) PPi(dx) for Borel A⊆[0,1].

[F5]

The expectation of an indicator is the probability of the event: an event indicator has expectation equal to its probability.

[F6]

Linearity, monotonicity, and the modulus bound for expectation: expectation is linear on finite sums of integrable terms.

[F7]

Expectation of a nonnegative or integrable random variable: expectation of a bounded measurable random variable is its integral under the law.

[F9]

Every nonempty at-most-countable set has a surjection from N (A nonempty set is at most countable iff it is a surjective image of N).

[A1]

The conditional-law version in [F1] has the monotonicity required by PRDS on the support of the marginal law of Pi.

[A2]

The standard-Borel conditional-law existence interface is used under the Axiom of Choice (The Axiom of Choice) as recorded in Positive regression dependence on true-null coordinates (PRDS).

Proof

technique · decompose by the rejection count and use PRDS to fold the conditional event probabilities

Given: m,q,P,I0,i as in the Statement.

1.1F2F5F6F7givenconstruct

Put ck=kq/m, Ak:={Pi≤ck}, and Bi,k:={P−i∈Ci,k}. If P(Ak)>0, set ak:=P(Ak∩Bi,k)/P(Ak); otherwise set ak=0. By [F2], Ii/(R∨1)=∑k=1mk−11Ak∩Bi,k. The terms are bounded and the sum is finite, so [F5]–[F7] give E[Ii/(R∨1)]=∑k=1m(P(Ak)/k)ak; a zero-probability Ak contributes zero by the definition of ak.

1.2F1A1A2F2given

For each k, lift Di,k to D~i,k:={p∈[0,1]m:p−i∈Di,k}. The coordinate-deletion map from [0,1]m to the remaining-coordinate product is measurable: the preimage of each measurable rectangle is a finite intersection of coordinate cylinders, and such rectangles generate the product sigma-algebra. Hence D~i,k is Borel, and it is coordinatewise increasing. Let gk(x):=Ki(x,D~i,k), nondecreasing on the support by [F1] and [A1]; the kernel exists on this standard-Borel interface under [A2].

1.3F1F8F9givenconstruct

Write Si=supp⁡(μi). The family U:={(a,b)∩[0,1]:a,b∈Q, a<b} is a basis for the relative topology on [0,1]. If U is relative open and x∈U, write U=O∩[0,1] with O open in R by [F8]; choose ε>0 with (x−ε,x+ε)⊆O using [F8], then use rational density from [F8] to choose a,b∈Q with x−ε<a<x<b<x+ε. Thus x∈(a,b)∩[0,1]⊆U. Since Q×Q is nonempty and at most countable by [F8], [F9] gives an enumeration ((an,bn))n∈N of it, whose interval images enumerate U; hence the basis is countable. Let En=(an,bn)∩[0,1] if an<bn and μi((an,bn)∩[0,1])=0, and En=∅ otherwise. By the definition of support in Positive regression dependence on true-null coordinates (PRDS), [0,1]∖Si=⋃n∈NEn. Indeed, a point outside the support has a relative open null neighborhood and hence a basis neighborhood contained in it, which occurs in the enumeration; conversely, membership in any such null basis neighborhood excludes support membership. The right-hand side is a countable union of null Borel sets, so [F8] gives μi([0,1]∖Si)=0. Thus Si is Borel and μi(Si)=1.

2.1F1A1F4F2step 1.3givenalgebra

By [F4], whenever P(Ak)>0, P(Ak∩{P−i∈Di,k})P(Ak)=∫[0,ck]gk(x) μi(dx)μi([0,ck]). For fixed k<m, this average is at most the corresponding average over [0,ck+1]. By step 1.3, both averages may be restricted to Si without changing them. Every supported x≤ck is below every supported y∈(ck,ck+1], so gk(x)≤gk(y) by [F1] and [A1]. The larger-cutoff average is a mixture of the first average and the average over the added interval; the latter is at least the first whenever it has positive mass, and if it has zero mass the two averages agree.

2.2F3step 1.1algebra

By [F3], P(Ak)≤ck=kq/m for every k. Substituting into step 1.1 yields E[Ii/(R∨1)]≤(q/m)∑k=1mak.

3.1F2F4step 1.1step 2.1givenalgebra

Let k0 be the first index with P(Ak0)>0, if one exists; then aj=0 for j<k0, and Ci,k0⊆Di,k0 gives ak0≤P(P−i∈Di,k0∣Ak0)≤1 by step 2.1. For k>k0, suppose ∑j<kaj≤P(P−i∈Di,k−1∣Ak−1). Since P(Ak−1)>0 and Ak−1⊆Ak, step 2.1 applied to the nondecreasing gk−1 makes this at most P(P−i∈Di,k−1∣Ak). Also P(Ak)>0, so [F4] gives ak=P(P−i∈Ci,k∣Ak). The disjoint union Di,k=Di,k−1 ∪˙ Ci,k from [F2] then yields ∑j≤kaj≤P(P−i∈Di,k∣Ak), completing the induction.

4.1F2step 2.2step 3.1algebra∎

If k0 exists, step 3.1 at k=m and Di,m equal to the whole space give ∑k=1mak≤1. If no such k0 exists, all P(Ak)=0 and every ak=0, so the same bound holds. Substituting into step 2.2 proves the contribution inequality.

Remarks

The algebraic contribution bound uses only the PRDS monotonicity for the finite family of sets D~i,k. The inherited Axiom of Choice is used to formulate the standard-Borel conditional-law interface; no choice is used in the finite event decomposition or induction.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

BH controls FDR under PRDS

Statement

Let E=((X,A),Θ,(Pθ)θ∈Θ) be a statistical experiment, let m≥1, and fix a finite family of null hypotheses H01,…,H0m with p-value statistics p1,…,pm valid for their respective nulls. For each θ, write

I0(θ):={i:θ∈H0i},m0(θ):=∣I0(θ)∣.

Assume the Axiom of Choice as required for the regular conditional-law interface in Positive regression dependence on true-null coordinates (PRDS). Suppose that, under every Pθ, the p-value vector (p1(X),…,pm(X)) is PRDS on I0(θ). Then for every q∈(0,1), the ordinary BH procedure in Benjamini–Hochberg step-up procedure satisfies

FDR⁡θ≤m0(θ)mq≤q.

The PRDS assumption is imposed only on the true-null coordinates; no independence assumption is made.

Facts & Assumptions

Given: A finite family of valid p-values, q∈(0,1), and under each Pθ the PRDS condition on the true-null set I0(θ). The PRDS regular conditional-law convention uses the Axiom of Choice as recorded in Positive regression dependence on true-null coordinates (PRDS).

[F1]

Null-valid p-values and familywise and false-discovery error rates: I0(θ) is the true-null index set, Vθ counts rejected true nulls, and FDR⁡θ=Eθ[Vθ/(R∨1)].

[F2]

Benjamini–Hochberg step-up procedure: BH takes the largest R with p(R)≤Rq/m and rejects exactly ranks 1,…,R.

[F3]

Positive regression dependence on true-null coordinates (PRDS): for each i∈I0(θ), every increasing Borel event has a conditional-probability version nondecreasing in pi on its support.

[F4]

A PRDS bound for each BH true-null contribution: under validity and PRDS on I0(θ), each true-null contribution satisfies Eθ[Ii/(R∨1)]≤q/m.

[F5]

Linearity, monotonicity, and the modulus bound for expectation: expectation is linear on finite sums of integrable random variables.

[F6]

Expectation of a nonnegative or integrable random variable: expectation is integration with respect to the specified law.

[A1]

Every p-value is valid under its own null, so each i∈I0(θ) meets the superuniformity hypothesis of [F4].

[A2]

Under every Pθ, the vector of all p-values is PRDS on the full set I0(θ), not merely pairwise positively correlated.

[A3]

The standard-Borel regular conditional-law existence interface assumes the Axiom of Choice (The Axiom of Choice) as stated in Positive regression dependence on true-null coordinates (PRDS).

Proof

technique · sum the true-null contributions

Given: The experiment, the fixed family and validity assumptions in the Statement, q∈(0,1), and the PRDS condition for every true-null set.

1.1F1F2F5F6givenconstruct

Fix θ∈Θ. Let Ii be the indicator that the BH rule [F2] rejects hypothesis i. By [F1], Vθ=∑i∈I0(θ)Ii and FDR⁡θ=Eθ[Vθ/(R∨1)]. The ratio is bounded by one, so it is integrable by [F6]; finite linearity [F5] gives FDR⁡θ=∑i∈I0(θ)Eθ[Ii/(R∨1)].

2.1F1F2F3F4A1A2A3step 1.1algebra∎

If I0(θ)=∅, step 1.1 is an empty sum and FDR is zero. Otherwise, for each i∈I0(θ), [A1] gives validity and [A2] gives PRDS on a set containing i under the AC-based conditional-law interface [A3], so [F4] bounds its contribution by q/m. Summing step 1.1 gives FDR⁡θ≤∣I0(θ)∣q/m=(m0(θ)/m)q≤q. Only the designated true-null coordinates are needed; independence is not assumed.

Remarks

The Axiom of Choice enters through the standard-Borel regular conditional-law interface that gives the stated PRDS condition its kernel formulation. The finite sum of null contributions uses no additional choice. Pairwise covariance information alone does not supply the hypothesis; the companion examples include a valid-p-value witness.

5 · Examples, counterexamples and false statements

None yet.

Sources