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The strong mixing coefficient satisfies α(n)≤1/4\alpha(n) \le 1/4α(n)≤1/4

Proved
MarkovChainCLT.alphaMixingCoef_le_quarter

by Gabewhigham · Sep 5, 2026 · Mathlib c5ea003 (Lean v4.30.0)

mixingprobabilitystationary-processes

Let PPP be a probability measure and let Y=(Yi)i≥0Y=(Y_i)_{i\ge0}Y=(Yi​)i≥0​ be a measurable sequence of random variables. Then the strong (α\alphaα-) mixing coefficient at every lag nnn obeys the universal bound

α(n) ≤ 14.\alpha(n)\ \le\ \tfrac14 .α(n) ≤ 41​.

Indeed, writing a=P(A)a=P(A)a=P(A), b=P(B)b=P(B)b=P(B) and c=P(A∩B)c=P(A\cap B)c=P(A∩B) for events AAA and BBB, one has 0≤c≤min⁡(a,b)0\le c\le\min(a,b)0≤c≤min(a,b) and c≥a+b−1c\ge a+b-1c≥a+b−1. Consequently

c−ab ≤ min⁡(a,b)(1−max⁡(a,b)) ≤ 14,ab−c ≤ max⁡(ab, (1−a)(1−b)) ≤ 14,c-ab\ \le\ \min(a,b)\bigl(1-\max(a,b)\bigr)\ \le\ \tfrac14,\qquad ab-c\ \le\ \max\bigl(ab,\,(1-a)(1-b)\bigr)\ \le\ \tfrac14,c−ab ≤ min(a,b)(1−max(a,b)) ≤ 41​,ab−c ≤ max(ab,(1−a)(1−b)) ≤ 41​,

so every element of the set defining α(n)\alpha(n)α(n) is at most 1/41/41/4, and so is its supremum. Together with nonnegativity this pins α(n)\alpha(n)α(n) to the interval [0,1/4][0,1/4][0,1/4], the normalisation under which the comparison α(n)≤ρ(n)/4\alpha(n)\le\rho(n)/4α(n)≤ρ(n)/4 is sharp.

Formalization Note Measurability of the YiY_iYi​ is assumed so that the events appearing in the definition, which are measurable for the generated past and future σ\sigmaσ-algebras, are measurable for the ambient σ\sigmaσ-algebra; this is what makes the inclusion-exclusion bound P(A)+P(B)−P(A∩B)≤1P(A)+P(B)-P(A\cap B)\le1P(A)+P(B)−P(A∩B)≤1 available.

Preamble
import Definitions.Def_MixingCoefficients

open MeasureTheory ProbabilityTheory MarkovChainCLT
open scoped ENNReal NNReal Topology ProbabilityTheory
Formal statement
theorem MarkovChainCLT.alphaMixingCoef_le_quarter {Ω E : Type*} [MeasurableSpace Ω]
    [MeasurableSpace E] (P : Measure Ω) [IsProbabilityMeasure P] (Y : ℕ → Ω → E)
    (hY : ∀ i, Measurable (Y i)) (n : ℕ) :
    alphaMixingCoef P Y n ≤ 1 / 4 := by sorry
Source
R. C. Bradley, "Basic Properties of Strong Mixing Conditions. A Survey and Some Open Questions", Probability Surveys 2 (2005) 107-144, eq. (1.10); see also G. L. Jones, "On the Markov Chain Central Limit Theorem", Probability Surveys 1 (2004) 299-320, Section 3, Definition 1.

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