mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Independence.Integration

Goal state before:
pp: Ω : Type u_1
𝕜 : Type u_2
inst✝¹⁴ : RCLike 𝕜
mΩ : MeasurableSpace Ω
μ : Measure Ω
𝓧 : Type u_3
𝓨 : Type u_4
E : Type u_5
F : Type u_6
G : Type u_7
inst✝¹³ : MeasurableSpace 𝓧
inst✝¹² : MeasurableSpace 𝓨
inst✝¹¹ : NormedAddCommGroup E
inst✝¹⁰ : NormedSpace ℝ E
inst✝⁹ : NormedSpace 𝕜 E
inst✝⁸ : CompleteSpace E
inst✝⁷ : NormedAddCommGroup F
inst✝⁶ : NormedSpace ℝ F
inst✝⁵ : NormedSpace 𝕜 F
inst✝⁴ : CompleteSpace F
inst✝³ : NormedAddCommGroup G
inst✝² : NormedSpace ℝ G
inst✝¹ : NormedSpace 𝕜 G
inst✝ : CompleteSpace G
X : Ω → 𝓧
Y : Ω → 𝓨
f : 𝓧 → E
g : 𝓨 → F
hXY : X ⟂ᵢ[μ] Y
hX : AEMeasurable X μ
hY : AEMeasurable Y μ
hf : Integrable f (Measure.map X μ)
hg : Integrable g (Measure.map Y μ)
B : E →L[𝕜] F →L[𝕜] G
h : ¬∀ᵐ (ω : Ω) ∂μ, f (X ω) = 0
this✝³ : MeasurableSpace E := borel E
this✝² : BorelSpace E
this✝¹ : MeasurableSpace F := borel F
this✝ : BorelSpace F
this : IsProbabilityMeasure μ
⊢ Continuous (Function.uncurry fun x1 x2 ↦ (B x1) x2)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: case e'_4
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : Ω → ℝ
hX : MemLp X 2 μ
c : ℝ
hc : 0 < c
⊢ eVar[X; μ] / ENNReal.ofReal (c ^ 2) = eVar[X; μ] / ↑c.toNNReal ^ 2

Tactic:
rw [ENNReal.ofReal_pow hc.le]
    rfl

Goal state after:
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: ι : Type u_2
inst✝¹ : Fintype ι
Ω : ι → Type u_3
mΩ : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (μ i)
X : (i : ι) → Ω i → ℝ
h : ∀ (i : ι), MemLp (X i) 2 (μ i)
i : ι
⊢ Measurable fun ω ↦ ω i

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsProbabilityMeasure μ
a b : ℝ
X : Ω → ℝ
h : ∀ᵐ (ω : Ω) ∂μ, X ω ∈ Set.Icc a b
hX : AEMeasurable X μ
ha : ∀ᵐ (ω : Ω) ∂μ, a ≤ X ω
hb : ∀ᵐ (ω : Ω) ∂μ, X ω ≤ b
hX_int₂ : Integrable (fun ω ↦ -X ω ^ 2) μ
hX_int₁ : Integrable (fun ω ↦ (a + b) * X ω) μ
⊢ Integrable (fun ω ↦ -X ω ^ 2 + (a + b) * X ω) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.HasLaw

Goal state before:
pp: Ω : Type u_1
𝓧 : Type u_2
mΩ : MeasurableSpace Ω
m𝓧 : MeasurableSpace 𝓧
X : Ω → 𝓧
μ : Measure 𝓧
P : Measure Ω
inst✝ : IsFiniteMeasure P
𝓨 : Type u_3
m𝓨 : MeasurableSpace 𝓨
ν : Measure 𝓨
Y : Ω → 𝓨
hX : HasLaw X μ P
hY : HasLaw Y ν P
h : X ⟂ᵢ[P] Y
⊢ AEMeasurable X P

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.HasLaw

Goal state before:
pp: Ω : Type u_1
𝓧 : Type u_2
mΩ : MeasurableSpace Ω
m𝓧 : MeasurableSpace 𝓧
X : Ω → 𝓧
μ : Measure 𝓧
P : Measure Ω
inst✝ : IsFiniteMeasure P
𝓨 : Type u_3
m𝓨 : MeasurableSpace 𝓨
ν : Measure 𝓨
Y : Ω → 𝓨
hX : HasLaw X μ P
hY : HasLaw Y ν P
h : X ⟂ᵢ[P] Y
⊢ AEMeasurable Y P

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.HasLaw

Goal state before:
pp: Ω : Type u_1
𝓧 : Type u_2
mΩ : MeasurableSpace Ω
m𝓧 : MeasurableSpace 𝓧
X : Ω → 𝓧
μ : Measure 𝓧
P : Measure Ω
inst✝ : IsFiniteMeasure P
𝓨 : Type u_3
m𝓨 : MeasurableSpace 𝓨
ν : Measure 𝓨
Y : Ω → 𝓨
hX : HasLaw X μ P
hY : HasLaw Y ν P
h : HasLaw (fun ω ↦ (X ω, Y ω)) (μ.prod ν) P
⊢ AEMeasurable X P

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.HasLaw

Goal state before:
pp: Ω : Type u_1
𝓧 : Type u_2
mΩ : MeasurableSpace Ω
m𝓧 : MeasurableSpace 𝓧
X : Ω → 𝓧
μ : Measure 𝓧
P : Measure Ω
inst✝ : IsFiniteMeasure P
𝓨 : Type u_3
m𝓨 : MeasurableSpace 𝓨
ν : Measure 𝓨
Y : Ω → 𝓨
hX : HasLaw X μ P
hY : HasLaw Y ν P
h : HasLaw (fun ω ↦ (X ω, Y ω)) (μ.prod ν) P
⊢ AEMeasurable Y P

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.HasLaw

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
P : Measure Ω
ι : Type u_3
inst✝ : Fintype ι
𝓧 : ι → Type u_4
m𝓧 : (i : ι) → MeasurableSpace (𝓧 i)
μ : (i : ι) → Measure (𝓧 i)
X : (i : ι) → Ω → 𝓧 i
hX : ∀ (i : ι), HasLaw (X i) (μ i) P
h : iIndepFun X P
⊢ ∀ (i : ι), AEMeasurable (X i) P

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.HasLaw

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
P : Measure Ω
inst✝¹ : IsProbabilityMeasure P
ι : Type u_3
inst✝ : Fintype ι
𝓧 : ι → Type u_4
m𝓧 : (i : ι) → MeasurableSpace (𝓧 i)
μ : (i : ι) → Measure (𝓧 i)
X : (i : ι) → Ω → 𝓧 i
hX : ∀ (i : ι), HasLaw (X i) (μ i) P
h : HasLaw (fun ω i ↦ X i ω) (Measure.pi μ) P
⊢ ∀ (i : ι), AEMeasurable (X i) P

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
inst✝⁵ : MeasurableSpace α
inst✝⁴ : MeasurableSpace β
inst✝³ : MeasurableSpace γ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
inst✝² : TopologicalSpace γ
inst✝¹ : PseudoMetrizableSpace γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
⊢ AEStronglyMeasurable g ν

Tactic:
refine aestronglyMeasurable_iff_aemeasurable_separable.2 ⟨h.aemeasurable_snd, ?_⟩

Goal state after:
α : Type u_1
β : Type u_2
γ : Type u_3
inst✝⁵ : MeasurableSpace α
inst✝⁴ : MeasurableSpace β
inst✝³ : MeasurableSpace γ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
inst✝² : TopologicalSpace γ
inst✝¹ : PseudoMetrizableSpace γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
⊢ ∃ t, IsSeparable t ∧ ∀ᵐ (x : β) ∂ν, g x ∈ t
Module: Mathlib.Probability.Independence.Integration

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
E : Type u_5
F : Type u_6
inst✝¹⁰ : TopologicalSpace E
inst✝⁹ : ContinuousENorm E
inst✝⁸ : MeasurableSpace E
inst✝⁷ : OpensMeasurableSpace E
inst✝⁶ : TopologicalSpace F
inst✝⁵ : ContinuousENorm F
inst✝⁴ : MeasurableSpace F
inst✝³ : OpensMeasurableSpace F
inst✝² : SMul E F
inst✝¹ : ContinuousSMul E F
inst✝ : ENormSMulClass E F
X : Ω → E
Y : Ω → F
hXY : X ⟂ᵢ[μ] Y
hX : Integrable X μ
hY : Integrable Y μ
⊢ Continuous (Function.uncurry fun x1 x2 ↦ x1 • x2)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝² : IsProbabilityMeasure μ'
mE : MeasurableSpace E
Z : Ω' → E
l : Filter ι
inst✝¹ : TopologicalSpace E
inst✝ : OpensMeasurableSpace E
hZ : AEMeasurable Z μ'
x✝ : ι
⊢ AEMeasurable Z μ'

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: case neg
α : Type u_1
β : Type u_2
γ : Type u_3
inst✝⁴ : MeasurableSpace α
inst✝³ : MeasurableSpace β
inst✝² : MeasurableSpace γ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
inst✝¹ : NormedAddCommGroup γ
inst✝ : OpensMeasurableSpace γ
h : IdentDistrib f g μ ν
p : ℝ≥0∞
h0 : ¬p = 0
h_top : ¬p = ∞
⊢ (∫⁻ (a : α), ‖f a‖ₑ ^ p.toReal ∂μ) ^ p.toReal⁻¹ = (∫⁻ (a : β), ‖g a‖ₑ ^ p.toReal ∂ν) ^ p.toReal⁻¹

Tactic:
congr 1

Goal state after:
case neg.e_a
α : Type u_1
β : Type u_2
γ : Type u_3
inst✝⁴ : MeasurableSpace α
inst✝³ : MeasurableSpace β
inst✝² : MeasurableSpace γ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
inst✝¹ : NormedAddCommGroup γ
inst✝ : OpensMeasurableSpace γ
h : IdentDistrib f g μ ν
p : ℝ≥0∞
h0 : ¬p = 0
h_top : ¬p = ∞
⊢ ∫⁻ (a : α), ‖f a‖ₑ ^ p.toReal ∂μ = ∫⁻ (a : β), ‖g a‖ₑ ^ p.toReal ∂ν
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝³ : IsProbabilityMeasure μ'
mE : MeasurableSpace E
Z : Ω' → E
l : Filter ι
inst✝² : TopologicalSpace E
inst✝¹ : l.IsCountablyGenerated
inst✝ : OpensMeasurableSpace E
X : ι → Ω' → E
hX₁ : ∀ (i : ι), AEMeasurable (X i) μ'
hZ : AEMeasurable Z μ'
hX₂ : ∀ᵐ (ω : Ω') ∂μ', Tendsto (fun i ↦ X i ω) l (𝓝 (Z ω))
f : BoundedContinuousFunction E NNReal
⊢ AEMeasurable (fun ω ↦ ↑(f ω)) (Measure.map Z μ')

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝³ : IsProbabilityMeasure μ'
mE : MeasurableSpace E
Z : Ω' → E
l : Filter ι
inst✝² : TopologicalSpace E
inst✝¹ : l.IsCountablyGenerated
inst✝ : OpensMeasurableSpace E
X : ι → Ω' → E
hX₁ : ∀ (i : ι), AEMeasurable (X i) μ'
hZ : AEMeasurable Z μ'
hX₂ : ∀ᵐ (ω : Ω') ∂μ', Tendsto (fun i ↦ X i ω) l (𝓝 (Z ω))
f : BoundedContinuousFunction E NNReal
i : ι
⊢ AEMeasurable (fun ω ↦ ↑(f ω)) (Measure.map (X i) μ')

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝³ : IsProbabilityMeasure μ'
mE : MeasurableSpace E
Z : Ω' → E
l : Filter ι
inst✝² : TopologicalSpace E
inst✝¹ : l.IsCountablyGenerated
inst✝ : OpensMeasurableSpace E
X : ι → Ω' → E
hX₁ : ∀ (i : ι), AEMeasurable (X i) μ'
hZ : AEMeasurable Z μ'
hX₂ : ∀ᵐ (ω : Ω') ∂μ', Tendsto (fun i ↦ X i ω) l (𝓝 (Z ω))
f : BoundedContinuousFunction E NNReal
⊢ ∀ (x : ι), AEMeasurable (fun a ↦ ↑(f (X x a))) μ'

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁴ : IsProbabilityMeasure μ'
mE : MeasurableSpace E
Z : Ω' → E
l : Filter ι
inst✝³ : PseudoEMetricSpace E
inst✝² : BorelSpace E
inst✝¹ : l.IsCountablyGenerated
inst✝ : l.NeBot
X : ι → Ω' → E
h : TendstoInMeasure μ' X l Z
hX : ∀ (i : ι), AEMeasurable (X i) μ'
hZ : AEMeasurable Z μ'
ns : ℕ → ι
hns : Tendsto ns atTop l
ms : ℕ → ℕ
hms1 : Tendsto ms atTop atTop
hms2 : ∀ᵐ (x : Ω') ∂μ', Tendsto (fun i ↦ (X ∘ ns) (ms i) x) atTop (𝓝 (Z x))
⊢ ∀ (i : ℕ), AEMeasurable (X (ns (ms i))) μ'

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Independence.Integration

Goal state before:
pp: Ω : Type u_5
𝓧 : Type u_6
m mΩ : MeasurableSpace Ω
P : Measure Ω
m𝓧 : MeasurableSpace 𝓧
X : Ω → 𝓧
A : Set Ω
E : Type u_7
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℝ E
hm : m ≤ mΩ
f : 𝓧 → E
hA1 : Indep m (MeasurableSpace.comap X m𝓧) P
hX : AEMeasurable X P
hA2 : MeasurableSet A
hf : AEStronglyMeasurable f (Measure.map X P)
⊢ AEStronglyMeasurable id (Measure.map (A.indicator 1) P)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
this : ∀ ε > 0, ∀ᶠ (n : ι) in l, |∫ (ω : E), F ω ∂Measure.map (Y n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'| < ↑L * ε
ε : ℝ
hε : ε > 0
⊢ ∀ᶠ (x : ι) in l, |∫ (ω : E), F ω ∂Measure.map (Y x) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'| < ε

Tactic:
convert! this (ε / L) (by positivity)

Goal state after:
ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
this : ∀ ε > 0, ∀ᶠ (n : ι) in l, |∫ (ω : E), F ω ∂Measure.map (Y n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'| < ↑L * ε
ε : ℝ
hε : ε > 0
x✝ : ι
⊢ ε = ↑L * (ε / ↑L)
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
⊢ AEStronglyMeasurable (fun x ↦ F (Y n x)) μ''

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
⊢ AEStronglyMeasurable (fun x ↦ F (X n x)) μ''

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
⊢ AEStronglyMeasurable (fun a ↦ F (Y n a) - F (X n a)) μ''

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
h_int_sub : Integrable (fun a ↦ ‖F (Y n a) - F (X n a)‖) μ''
⊢ AEMeasurable (Y n) μ''

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
h_int_sub : Integrable (fun a ↦ ‖F (Y n a) - F (X n a)‖) μ''
⊢ AEStronglyMeasurable F (Measure.map (Y n) μ'')

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
h_int_sub : Integrable (fun a ↦ ‖F (Y n a) - F (X n a)‖) μ''
⊢ AEMeasurable (X n) μ''

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
h_int_sub : Integrable (fun a ↦ ‖F (Y n a) - F (X n a)‖) μ''
⊢ AEStronglyMeasurable F (Measure.map (X n) μ'')

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : Type u_8
m : MeasurableSpace β
inst✝¹ : CommMonoid β
inst✝ : MeasurableMul₂ β
f : ι → Ω → β
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), Measurable (f i)
s : Finset ι
i : ι
hi : i ∉ s
h_right : f i = (fun p ↦ p ⟨i, ⋯⟩) ∘ fun a j ↦ f (↑j) a
h_meas_right : Measurable fun p ↦ p ⟨i, ⋯⟩
a : Ω
⊢ ∏ j, f (↑j) a = (∏ j, f ↑j) a

Tactic:
rw [Finset.prod_apply]

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
h_int_sub : Integrable (fun a ↦ ‖F (Y n a) - F (X n a)‖) μ''
⊢ AEMeasurable (fun x ↦ ‖Y n x - X n x‖) μ''

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
h_int_sub : Integrable (fun a ↦ ‖F (Y n a) - F (X n a)‖) μ''
⊢ AEMeasurable (fun x ↦ ε / 2) μ''

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.Floor

Goal state before:
pp: R : Type u_2
inst✝⁷ : Ring R
inst✝⁶ : LinearOrder R
inst✝⁵ : FloorRing R
inst✝⁴ : TopologicalSpace R
inst✝³ : OrderTopology R
inst✝² : MeasurableSpace R
inst✝¹ : IsStrictOrderedRing R
inst✝ : BorelSpace R
⊢ Measurable Int.fract

Tactic:
intro s hs
  rw [Int.preimage_fract]
  exact MeasurableSet.iUnion fun z => measurable_id.sub_const _ (hs.inter measurableSet_Ico)

Goal state after:
Module: Mathlib.Probability.Process.Filtration

Goal state before:
pp: case pos
Ω : Type u_1
ι : Type u_2
m : MeasurableSpace Ω
inst✝ : Preorder ι
s : Set (Filtration ι m)
i : ι
f : Filtration ι m
hf_mem : f ∈ s
⊢ sInf ((fun f ↦ ↑f i) '' s) ≤ m

Tactic:
exact le_trans (sInf_le ⟨f, hf_mem, rfl⟩) (f.le i)

Goal state after: