The strong mixing coefficient satisfies
ProvedMarkovChainCLT.alphaMixingCoef_le_quartermixingprobabilitystationary-processes
Let be a probability measure and let be a measurable sequence of random variables. Then the strong (-) mixing coefficient at every lag obeys the universal bound
Indeed, writing , and for events and , one has and . Consequently
so every element of the set defining is at most , and so is its supremum. Together with nonnegativity this pins to the interval , the normalisation under which the comparison is sharp.
Formalization Note Measurability of the is assumed so that the events appearing in the definition, which are measurable for the generated past and future -algebras, are measurable for the ambient -algebra; this is what makes the inclusion-exclusion bound 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 sorrySource
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.