OAI/Probability/InvariantIsing/Haar/MedianMean.lean

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3 declarations, 0 contain sorry, 0 declared as axioms

Relating the deterministic medians and means in the concentration step.

  1. lemma OAI.InvariantIsing.abs_median_le_bound line 14
  2. lemma OAI.InvariantIsing.abs_integral_sub_le_deviation_tail line 43

    Source documentation

    A bounded deviation has mean at most r plus its bound times the r-tail.

    lemma abs_integral_sub_le_deviation_tail {Ω : Type*} [MeasurableSpace Ω]
        (μ : Measure Ω) [IsProbabilityMeasure μ] (f : Ω → ℝ) (hf : Measurable f)
        (hfi : Integrable f μ) (m B r : ℝ) (hr : 0 ≤ r)
        (hB : ∀ ω, |f ω - m| ≤ B) :
        |(∫ ω, f ω ∂μ) - m| ≤ r + B * μ.real {ω | r ≤ |f ω - m|} := by
    …
  3. theorem OAI.InvariantIsing.tendsto_mean_sub_median_zero line 73

    Source documentation

    Uniformly bounded observables with exponential tails about their medians have means and medians asymptotically equal.

    theorem tendsto_mean_sub_median_zero {Ω : Type*} [MeasurableSpace Ω]
        (μ : Measure Ω) [IsProbabilityMeasure μ] (f : ℕ → Ω → ℝ) (hf : ∀ n, Measurable (f n))
        (m : ℕ → ℝ) (B : ℝ) (hB : 0 ≤ B) (hbound : ∀ n ω, |f n ω| ≤ B)
        (hl : ∀ n, (1 / 2 : ℝ) ≤ μ.real {ω | f n ω ≤ m n})
        (hu : ∀ n, (1 / 2 : ℝ) ≤ μ.real {ω | m n ≤ f n ω})
        (htail : ∀ r : ℝ, 0 < r → ∃ C a : ℝ, 0 ≤ C ∧ 0 < a ∧
          ∀ n, μ.real {ω | r ≤ |f n ω - m n|} ≤ C * Real.exp (-a * (n : ℝ))) :
        Tendsto (fun n => (∫ ω, f n ω ∂μ) - m n) atTop (𝓝 0) := by
    …