Documentation

BrownianMotion.Auxiliary.MeasureTheory

Measure theory lemmas to be upstreamed to Mathlib #

theorem Filter.EventuallyEq.div' {α : Type u_1} {β : Type u_2} [Div β] {f f' g g' : αβ} {l : Filter α} (h : f =ᶠ[l] g) (h' : f' =ᶠ[l] g') :
f / f' =ᶠ[l] g / g'
theorem Filter.EventuallyEq.sub' {α : Type u_1} {β : Type u_2} [Sub β] {f f' g g' : αβ} {l : Filter α} (h : f =ᶠ[l] g) (h' : f' =ᶠ[l] g') :
f - f' =ᶠ[l] g - g'
theorem ProbabilityTheory.variance_pi {ι : Type u_1} [Fintype ι] {Ω : ιType u_2} { : (i : ι) → MeasurableSpace (Ω i)} {μ : (i : ι) → MeasureTheory.Measure (Ω i)} [∀ (i : ι), MeasureTheory.IsProbabilityMeasure (μ i)] {X : (i : ι) → Ω i} (h : ∀ (i : ι), MeasureTheory.MemLp (X i) 2 (μ i)) :
variance (∑ i : ι, fun (ω : (i : ι) → Ω i) => X i (ω i)) (MeasureTheory.Measure.pi μ) = i : ι, variance (X i) (μ i)
theorem ProbabilityTheory.centralMoment_of_integral_id_eq_zero {Ω : Type u_1} { : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω} (p : ) (hX : (x : Ω), X x μ = 0) :
centralMoment X p μ = (ω : Ω), X ω ^ p μ
@[simp]
theorem zero_mem_parallelepiped {ι : Type u_1} {E : Type u_2} [Fintype ι] [AddCommGroup E] [Module E] {v : ιE} :
@[simp]
theorem nonempty_parallelepiped {ι : Type u_1} {E : Type u_2} [Fintype ι] [AddCommGroup E] [Module E] {v : ιE} :
theorem ProbabilityTheory.covariance_fun_add_left {Ω : Type u_1} { : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X Y Z : Ω} [MeasureTheory.IsFiniteMeasure μ] (hX : MeasureTheory.MemLp X 2 μ) (hY : MeasureTheory.MemLp Y 2 μ) (hZ : MeasureTheory.MemLp Z 2 μ) :
covariance (fun (ω : Ω) => X ω + Y ω) Z μ = covariance (fun (ω : Ω) => X ω) Z μ + covariance (fun (ω : Ω) => Y ω) Z μ
theorem ProbabilityTheory.covariance_fun_add_right {Ω : Type u_1} { : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X Y Z : Ω} [MeasureTheory.IsFiniteMeasure μ] (hX : MeasureTheory.MemLp X 2 μ) (hY : MeasureTheory.MemLp Y 2 μ) (hZ : MeasureTheory.MemLp Z 2 μ) :
covariance X (fun (ω : Ω) => Y ω + Z ω) μ = covariance X (fun (ω : Ω) => Y ω) μ + covariance X (fun (ω : Ω) => Z ω) μ
theorem ProbabilityTheory.covariance_fun_sub_left {Ω : Type u_1} { : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X Y Z : Ω} [MeasureTheory.IsFiniteMeasure μ] (hX : MeasureTheory.MemLp X 2 μ) (hY : MeasureTheory.MemLp Y 2 μ) (hZ : MeasureTheory.MemLp Z 2 μ) :
covariance (fun (ω : Ω) => X ω - Y ω) Z μ = covariance X Z μ - covariance Y Z μ
theorem ProbabilityTheory.covariance_fun_sub_right {Ω : Type u_1} { : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X Y Z : Ω} [MeasureTheory.IsFiniteMeasure μ] (hX : MeasureTheory.MemLp X 2 μ) (hY : MeasureTheory.MemLp Y 2 μ) (hZ : MeasureTheory.MemLp Z 2 μ) :
covariance X (fun (ω : Ω) => Y ω - Z ω) μ = covariance X (fun (ω : Ω) => Y ω) μ - covariance X (fun (ω : Ω) => Z ω) μ
theorem ProbabilityTheory.covariance_fun_div_left {Ω : Type u_1} { : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X Y : Ω} (c : ) :
covariance (fun (ω : Ω) => X ω / c) Y μ = covariance X Y μ / c
theorem ProbabilityTheory.covariance_fun_div_right {Ω : Type u_1} { : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X Y : Ω} (c : ) :
covariance X (fun (ω : Ω) => Y ω / c) μ = covariance X Y μ / c
theorem ProbabilityTheory.variance_fun_div {Ω : Type u_1} { : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω} (c : ) (hX : AEMeasurable X μ) :
variance (fun (ω : Ω) => X ω / c) μ = variance X μ / c ^ 2
theorem MeasurableSpace.comap_process {Ω : Type u_1} {T : Type u_2} {𝓧 : TType u_3} [(t : T) → MeasurableSpace (𝓧 t)] (X : (t : T) → Ω𝓧 t) :
MeasurableSpace.comap (fun (ω : Ω) (t : T) => X t ω) pi = ⨆ (t : T), MeasurableSpace.comap (X t) inferInstance
theorem MeasurableSpace.comap_le_comap {Ω : Type u_1} {𝓧 : Type u_2} {𝓨 : Type u_3} [m𝓧 : MeasurableSpace 𝓧] [m𝓨 : MeasurableSpace 𝓨] {X : Ω𝓧} {Y : Ω𝓨} (f : 𝓧𝓨) (hf : Measurable f) (h : Y = f X) :
theorem MeasureTheory.Filtration.natural_eq_comap {Ω : Type u_1} {ι : Type u_2} {m : MeasurableSpace Ω} {β : ιType u_3} [(i : ι) → TopologicalSpace (β i)] [∀ (i : ι), TopologicalSpace.MetrizableSpace (β i)] [ : (i : ι) → MeasurableSpace (β i)] [∀ (i : ι), BorelSpace (β i)] [Preorder ι] (u : (i : ι) → Ωβ i) (hum : ∀ (i : ι), StronglyMeasurable (u i)) (i : ι) :
(natural u hum) i = MeasurableSpace.comap (fun (ω : Ω) (j : (Set.Iic i)) => u (↑j) ω) inferInstance
theorem ProbabilityTheory.measure_eq_zero_or_one_of_indep_self {Ω : Type u_1} {m : MeasurableSpace Ω} {P : MeasureTheory.Measure Ω} [MeasureTheory.IsZeroOrProbabilityMeasure P] (hm1 : m ) (hm2 : Indep m m P) {A : Set Ω} (hA : MeasurableSet A) :
P A = 0 P A = 1
theorem ProbabilityTheory.singleton_indepSets_comap_iff {Ω : Type u_1} { : MeasurableSpace Ω} {P : MeasureTheory.Measure Ω} [MeasureTheory.IsZeroOrProbabilityMeasure P] {𝓧 : Type u_2} {m𝓧 : MeasurableSpace 𝓧} {A : Set Ω} {X : Ω𝓧} (hX : Measurable X) (hA : MeasurableSet A) :
theorem IndepSets.setIntegral_eq_mul {Ω : Type u_1} {𝓧 : Type u_2} { : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {m𝓧 : MeasurableSpace 𝓧} {X : Ω𝓧} [MeasureTheory.IsZeroOrProbabilityMeasure μ] {f : 𝓧} {A : Set Ω} (hA1 : ProbabilityTheory.IndepSets {A} {s : Set Ω | MeasurableSet s} μ) (hX : Measurable X) (hA2 : MeasurableSet A) (hf : MeasureTheory.AEStronglyMeasurable f (MeasureTheory.Measure.map X μ)) :
(ω : Ω) in A, f (X ω) μ = μ.real A * (ω : Ω), f (X ω) μ
theorem measurableSpace_le_iff {Ω : Type u_1} {m1 m2 : MeasurableSpace Ω} :
m1 m2 ∀ (s : Set Ω), MeasurableSet sMeasurableSet s