Maximal-correlation submultiplicativity from a two-sided conditional-expectation representative
ProvedMarkovChainCLT.rhoMixingCoef_submultiplicative_of_condExp_bridgeconditional-expectationmarkov-chainsmixingprobability
Let be a measurable process on a probability space. Suppose that for every square-integrable future random variable , its conditional expectation given the history through the intermediate time has a version that is measurable both with respect to that history and with respect to the future beginning at . Then the maximal-correlation coefficients satisfy
This version-based formulation is insensitive to the almost-everywhere choice of conditional-expectation representative and is the form naturally supplied by the Markov property, where can be chosen as a measurable function of the state at time .
Preamble
import Definitions.Def_MixingCoefficients import Theorems.Thm_MarkovChainCLT_rhoMixingCoef_nonneg_le_one_of_finite import Mathlib.MeasureTheory.Function.ConditionalExpectation.PullOut import Mathlib.Probability.CondVar import Mathlib.MeasureTheory.Integral.MeanInequalities open MeasureTheory ProbabilityTheory Filter open scoped ENNReal NNReal Topology ProbabilityTheory open MarkovChainCLT
Formal statement
theorem MarkovChainCLT.rhoMixingCoef_submultiplicative_of_condExp_bridge
{Ω E : Type*} [mΩ : MeasurableSpace Ω] [mE : MeasurableSpace E]
(P : @Measure Ω mΩ) [IsProbabilityMeasure P] (Y : ℕ → Ω → E)
(hY : ∀ i, Measurable (Y i))
(hcond : ∀ (k m n : ℕ) (V : Ω → ℝ),
Measurable[processSigma Y (Set.Ici (k + (m + n)))] V →
MemLp V 2 P →
∃ W : Ω → ℝ,
Measurable[processSigma Y (Set.Iic (k + m))] W ∧
Measurable[processSigma Y (Set.Ici (k + m))] W ∧
W =ᵐ[P] MeasureTheory.condExp (m₀ := mΩ)
(processSigma Y (Set.Iic (k + m))) P V) :
∀ m n : ℕ,
rhoMixingCoef P Y (m + n) ≤ rhoMixingCoef P Y m * rhoMixingCoef P Y n := by sorrySource
Richard C. Bradley, Basic Properties of Strong Mixing Conditions. A Survey and Some Open Questions, arXiv:math/0511078 (updated survey version arXiv:1403.4895), p. 4, equations (1.10)–(1.11). This theorem isolates the version-invariant conditional-expectation argument behind equation (1.11).