Measure Real exists abs lt le
ProbabilityTheory.measureReal_exists_abs_lt_le
Plain-language statement
Maximal inequality: the probability that |X| exceeds lam somewhere on a finite set F ⊆ Iic t is at most K / lam, with K independent of F.
Exact Lean statement
lemma measureReal_exists_abs_lt_le [OrderBot ι] [IsFiniteMeasure μ]
(hX : StronglyAdapted 𝓕 X) (hXint : ∀ s, Integrable (X s) μ) {C : ℝ}
(hC : ∀ S : ElementaryPredictableSet 𝓕, μ[(S.indicator (1 : ℝ) ● X) t] ≤ C)
(hlam : 0 < lam) (hF : ∀ s ∈ F, s ≤ t) :
μ.real {ω | ∃ s ∈ F, lam < |X s ω|}
≤ 2 * (C + ∫ ω, |X t ω - X ⊥ ω| ∂μ + ∫ ω, |X ⊥ ω| ∂μ + ∫ ω, |X t ω| ∂μ) / lamFormal artifact
Lean source
lemma measureReal_exists_abs_lt_le [OrderBot ι] [IsFiniteMeasure μ] (hX : StronglyAdapted 𝓕 X) (hXint : ∀ s, Integrable (X s) μ) {C : ℝ} (hC : ∀ S : ElementaryPredictableSet 𝓕, μ[(S.indicator (1 : ℝ) ● X) t] ≤ C) (hlam : 0 < lam) (hF : ∀ s ∈ F, s ≤ t) : μ.real {ω | ∃ s ∈ F, lam < |X s ω|} ≤ 2 * (C + ∫ ω, |X t ω - X ⊥ ω| ∂μ + ∫ ω, |X ⊥ ω| ∂μ + ∫ ω, |X t ω| ∂μ) / lam := by set G : Finset ι := insert ⊥ F with hG have hGF : F ⊆ G := subset_insert _ _ have hGle : ∀ s ∈ G, s ≤ t := by simp [G]; grind set n : ℕ := G.card with hn set idx : ℕ → ι := finIdx G t with hidx have hmono : Monotone idx := finIdx_monotone hGle have hidx0 : idx 0 = ⊥ := finIdx_zero_eq_bot (mem_insert_self _ _) have hidxn : idx n = t := finIdx_eq_of_card_le hn.ge -- two-sided expectation bound for adapted 0/1 weights along `idx` have hbdd : ∀ W : ℕ → Ω → ℝ, (∀ k, k < n → ∀ ω, W k ω = 0 ∨ W k ω = 1) → (∀ k, k < n → Measurable[𝓕 (idx k)] (W k)) → ∫ ω, (∑ k ∈ range n, W k ω * (X (idx (k + 1)) ω - X (idx k) ω)) ∂μ ∈ Set.Icc (-(C + ∫ ω, |X (idx n) ω - X (idx 0) ω| ∂μ)) C := fun W hW01 hWmeas ↦ integral_sum_weight_increments_mem_Icc (t := t) hXint hC hmono (finIdx_le hGle) hW01 hWmeas -- apply the one-sided maximal inequality to `X` have hpos := mul_measureReal_exists_lt_le (lam := lam) hX hXint (n := n) hmono (K := C) (fun W hW01 hWmeas ↦ (hbdd W hW01 hWmeas).2) -- and to `-X` have hnegX : StronglyAdapted 𝓕 (fun s ω ↦ -X s ω) := fun s ↦ (hX s).neg have hnegint : ∀ s, Integrable ((fun s ω ↦ -X s ω) s) μ := fun s ↦ (hXint s).neg have hneg := mul_measureReal_exists_lt_le (lam := lam) hnegX hnegint (n := n) hmono (K := C + ∫ ω, |X (idx n) ω - X (idx 0) ω| ∂μ) (fun W hW01 hWmeas ↦ by have h1 := (hbdd W hW01 hWmeas).1 have h2 : ∫ ω, (∑ k ∈ range n, W k ω * (-X (idx (k + 1)) ω - -X (idx k) ω)) ∂μ = -∫ ω, (∑ k ∈ range n, W k ω * (X (idx (k + 1)) ω - X (idx k) ω)) ∂μ := by rw [← integral_neg] congr 1 with ω rw [← sum_neg_distrib] grind rw [h2] linarith) -- combine the two events have hsub : {ω | ∃ s ∈ F, lam < |X s ω|} ⊆ {ω | ∃ k ≤ n, lam < X (idx k) ω} ∪ {ω | ∃ k ≤ n, lam < -X (idx k) ω} := by rintro ω ⟨s, hs, habs⟩ obtain ⟨k, hk, hkeq⟩ := exists_finIdx_eq (t := t) (hGF hs) grind have habs u : ∫ ω, |(fun s ω ↦ -X s ω) u ω| ∂μ = ∫ ω, |X u ω| ∂μ := by simp rw [hidx0, hidxn] at hpos hneg rw [habs ⊥, habs t] at hneg have hunion : μ.real {ω | ∃ s ∈ F, lam < |X s ω|} ≤ μ.real {ω | ∃ k ≤ n, lam < X (idx k) ω} + μ.real {ω | ∃ k ≤ n, lam < -X (idx k) ω} := (measureReal_mono hsub).trans (measureReal_union_le _ _) have hI : (0 : ℝ) ≤ ∫ ω, |X t ω - X ⊥ ω| ∂μ := integral_nonneg fun ω ↦ abs_nonneg _ rw [le_div_iff₀ hlam] have hmul : lam * μ.real {ω | ∃ s ∈ F, lam < |X s ω|} ≤ lam * (μ.real {ω | ∃ k ≤ n, lam < X (idx k) ω} + μ.real {ω | ∃ k ≤ n, lam < -X (idx k) ω}) := mul_le_mul_of_nonneg_left hunion hlam.le rw [mul_add] at hmul nlinarith [hpos, hneg, hmul]- Project
- Brownian motion
- License
- Apache-2.0
- Commit
- 5077304f5e73
- Source
- BrownianMotion/StochasticIntegral/Quasimartingale/MaximalInequality.lean:653-711
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Person-level attribution pending.
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Project documentation
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Person-level attribution pending.