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Sample-covariance resolvent deterministic equivalents

Statement

Assume the Axiom of Choice. Let (ξij)i,j≥1 be one infinite iid array of complex random variables with Eξ11=0, E∣ξ11∣2=1, and E∣ξ11∣4<∞. For each positive integer n, let Nn be positive with n/Nn→c∈(0,∞) and let Xn=(ξij)1≤i≤n, 1≤j≤Nn be its upper-left block. Let Tn be deterministic Hermitian positive semidefinite with uniformly bounded operator norm and empirical eigenvalue measures Hn=n−1∑iδλi(Tn)⇒H. Let xn∈Cn be deterministic unit vectors such that, for every w∈C∖[0,∞), xn∗(Tn−wIn)−1xn⟶mH(w):=∫[0,∞)(t−w)−1 dH(t). Define An=Nn−1Tn1/2XnXn∗Tn1/2 and μnxn(B)=xn∗1B(An)xn for Borel B⊆[0,∞). Then almost surely μnxn converges weakly to the probability measure Fc,H whose Stieltjes transform is the unique m∈C satisfying Im⁡m>0, u=−(1−c)/z+cm with Im⁡u>0, and m=∫[0,∞)1t(1−c−czm)−z dH(t),Im⁡z>0.

Statement references

Bai, Miao, and Pan, Theorem 1 and complete Section 2 proof, printed pp. 8–16 (full paper PDF).

Silverstein, Theorem 1.1 and complete Section 3 proof (full paper PDF).

Facts & Assumptions

Given: The common nested iid array, finite-fourth-moment law, deterministic population matrices and directions, aspect ratio, and AC in the Statement.

[A1]

The Axiom of Choice permits a choice function for every family of nonempty sets (The Axiom of Choice).

[F1]

For bounded complex iid entries with the stated population and direction hypotheses, the directional measures converge almost surely to Fc,H (Directional deterministic equivalent for bounded sample-covariance entries).

[F2]

For a centered complex iid finite-fourth-moment array with E∣ξ11∣2=τ2, the same nested-block and aspect-ratio conventions give lim sup⁡∥Xn∥op/Nn≤(σR+σI)(1+c)≤2τ(1+c) almost surely, where σR2=E(Re⁡ξ11)2 and σI2=E(Im⁡ξ11)2; the bound includes τ=0 (A coarse complex sample-covariance norm bound from real edge bounds).

[F3]

A Hermitian directional spectral measure is a probability law (A Hermitian directional spectral measure is a probability law).

[F4]

Tight probability laws on a Polish space have weakly convergent subsequences under AC (Prokhorov tightness theorem on polish spaces).

[F5]

Equal Stieltjes transforms determine probability measures on the real line (Stieltjes inversion and uniqueness for probability measures on the real line).

[F6]

A Polish space is a separable topological space whose topology is induced by a complete metric (Polish spaces are separable completely metrizable spaces).

[F7]

Iid entries are mutually independent and share one common law (Identical distribution and IID families).

[F8]

The directional measure is ∑λ∥Pλxn∥22δλ for a deterministic unit vector (Directional spectral measure of a Hermitian matrix).

[F9]

The Stieltjes transform convention is mμ(z)=∫(t−z)−1dμ(t) on C+ (Stieltjes transform of a probability measure on the real line).

[F10]

Weak convergence means convergence of integrals against all bounded continuous real-valued functions (Weak convergence of borel probability measures).

[F11]

The operator norm is the maximum of ∥Av∥2 over unit vectors in the domain (The operator norm is zero on the zero domain and otherwise is max_{||v||=1} ||Tv||).

Proof

1.1givenF1F2F7algebra

Let ξ have the common entry law. For integer K, set ξ(K)=ξ1{∣ξ∣≤K}−E[ξ1{∣ξ∣≤K}], σK2=E∣ξ(K)∣2, and Δ(K)=ξ−ξ(K). Then σK→1, and τK2:=E∣Δ(K)∣2→0 because Eξ=0 and E∣ξ∣2<∞. For all sufficiently large K, σK>0; put ζ(K)=ξ(K)/σK. These entries are centered, bounded, iid and have unit second absolute moment, while Δ(K) is centered iid with finite fourth moment. At matrix level, Xn=σKZn(K)+Dn(K), where Zn(K) and Dn(K) are the common upper-left blocks formed from ζ(K) and Δ(K).

2.1givenF2F11step 1.1algebra

For each fixed sufficiently large integer K, the original, standardized, and residual arrays have second absolute moments 1, 1, and τK2, respectively. Applying the variance-scaled bound [F2] to each gives almost surely lim sup⁡n∥Xn∥Nn≤Cc,lim sup⁡n∥Zn(K)∥Nn≤Cc,lim sup⁡n∥Dn(K)∥Nn≤CcτK, where Cc=2(1+c). If τK=0, the centered residual entries are zero almost surely; countability of the double array gives Dn(K)=0 for every n on one probability-one event, so the residual bound still holds. Intersect these events over the countable set of such K. Writing An(K)=Nn−1Tn1/2Zn(K)Zn(K)∗Tn1/2, the identity UU∗−VV∗=(U−V)U∗+V(U−V)∗ yields lim sup⁡n∥An−σK2An(K)∥op≤MCc2(1+σK)τK,lim sup⁡n∥σK2An(K)−An(K)∥op≤MCc2∣σK2−1∣, where M=sup⁡n∥Tn∥op. For positive semidefinite B,C and z∈C+, the resolvent identity gives ∥(B−zI)−1−(C−zI)−1∥op≤∥B−C∥op/(Im⁡z)2.

3.1givenF1F9step 1.1step 2.1algebra

Fix z∈C+ and a deterministic unit direction sequence xn. For each such K, [F1] applied to Zn(K) gives xn∗(An(K)−zI)−1xn→mc,H(z) almost surely, with the transform convention [F9]. By step 2.1, lim sup⁡n∣xn∗(An−zI)−1xn−mc,H(z)∣≤MCc2(Im⁡z)2((1+σK)τK+∣σK2−1∣) on the probability-one event obtained by intersecting the events from step 2.1 with the almost-sure convergence event for this fixed truncation level. The right side tends to zero as K→∞, so the directional Stieltjes transforms converge almost surely at every fixed z∈C+. Intersecting over a countable dense set gives simultaneous convergence there.

4.1givenA1F2F3F4F5F6F8F10F11step 3.1algebra∎

By [F2], ∥An∥op≤M∥Xn∥op2/Nn is almost surely eventually bounded. Thus the directional laws are eventually supported on one compact interval; [F3] makes them probability measures and [F8] gives their exact spectral-measure meaning. They are therefore tight. The half-line is Polish: it is closed in the complete real line and has dense subset Q∩[0,∞), as required by [F6]. By [A1] and [F4], each subsequence has a weakly convergent further subsequence. Its transform equals mc,H on the dense set by step 3.1; continuity of Stieltjes transforms extends equality to C+, and [F5] identifies the subsequential limit as Fc,H. The bounded-continuous-test definition [F10] yields the stated weak convergence. Every subsequence has the same further limit, proving the asserted almost-sure limit.

Source notes

Bai, Miao, and Pan, Theorem 1 and Section 2, printed pp. 8–16 (full paper PDF). The sampling convention is the upper-left block of one iid double array. The truncation comparison uses the separately proved real-edge norm supplier; it does not assume weak convergence alone controls spectral edges.

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