mathlib-initiative/mathlib-tactics huggingface dataset:
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
⊢ Measure.pi μ = Measure.pi fun i ↦ map (X i) P

Tactic:
]

Goal state after:
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
⊢ Measure.pi μ = Measure.pi fun i ↦ map (X i) P
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: E : Type u_3
F : Type u_4
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
mE : MeasurableSpace E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace ℝ F
mF : MeasurableSpace F
μ : Measure E
inst✝¹ : IsProbabilityMeasure μ
ν : Measure F
inst✝ : IsProbabilityMeasure ν
L : StrongDual ℝ (E × F)
hLμ : MemLp (⇑(L ∘SL ContinuousLinearMap.inl ℝ E F)) 2 μ
hLν : MemLp (⇑(L ∘SL ContinuousLinearMap.inr ℝ E F)) 2 ν
x✝ : E × F
⊢ L x✝ = L x✝

Tactic:
]

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
δ : Type u_4
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSpace β
inst✝¹ : MeasurableSpace γ
inst✝ : MeasurableSpace δ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
u : γ → δ
h : IdentDistrib f g μ ν
hu : AEMeasurable u (Measure.map g ν)
⊢ AEMeasurable (u ∘ g) ν

Tactic:
]

Goal state after:
α : Type u_1
β : Type u_2
γ : Type u_3
δ : Type u_4
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSpace β
inst✝¹ : MeasurableSpace γ
inst✝ : MeasurableSpace δ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
u : γ → δ
h : IdentDistrib f g μ ν
hu : AEMeasurable u (Measure.map g ν)
⊢ AEMeasurable (u ∘ g) ν
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
δ : Type u_4
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSpace β
inst✝¹ : MeasurableSpace γ
inst✝ : MeasurableSpace δ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
u : γ → δ
h : IdentDistrib f g μ ν
hu : AEMeasurable u (Measure.map f μ)
⊢ Measure.map u (Measure.map g ν) = Measure.map u (Measure.map g ν)

pp: α : Type u_1
β : Type u_2
γ : Type u_3
δ : Type u_4
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSpace β
inst✝¹ : MeasurableSpace γ
inst✝ : MeasurableSpace δ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
u : γ → δ
h : IdentDistrib f g μ ν
hu : AEMeasurable u (Measure.map f μ)
⊢ AEMeasurable u (Measure.map g ν)

Tactic:
]

Goal state after:
α : Type u_1
β : Type u_2
γ : Type u_3
δ : Type u_4
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSpace β
inst✝¹ : MeasurableSpace γ
inst✝ : MeasurableSpace δ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
u : γ → δ
h : IdentDistrib f g μ ν
hu : AEMeasurable u (Measure.map f μ)
⊢ AEMeasurable u (Measure.map g ν)
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
δ : Type u_4
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSpace β
inst✝¹ : MeasurableSpace γ
inst✝ : MeasurableSpace δ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
u : γ → δ
h : IdentDistrib f g μ ν
hu : AEMeasurable u (Measure.map f μ)
⊢ AEMeasurable u (Measure.map f μ)

Tactic:
]

Goal state after:
α : Type u_1
β : Type u_2
γ : Type u_3
δ : Type u_4
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSpace β
inst✝¹ : MeasurableSpace γ
inst✝ : MeasurableSpace δ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
u : γ → δ
h : IdentDistrib f g μ ν
hu : AEMeasurable u (Measure.map f μ)
⊢ AEMeasurable u (Measure.map f μ)
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
inst✝² : MeasurableSpace α
inst✝¹ : MeasurableSpace β
inst✝ : MeasurableSpace γ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
h : IdentDistrib f g μ ν
s : Set γ
hs : MeasurableSet s
⊢ (Measure.map g ν) s = (Measure.map g ν) s

Tactic:
]

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
inst✝² : MeasurableSpace α
inst✝¹ : MeasurableSpace β
inst✝ : MeasurableSpace γ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
h : IdentDistrib f g μ ν
p : γ → Prop
pmeas : MeasurableSet {x | p x}
hp : ∀ᵐ (x : α) ∂μ, p (f x)
⊢ ∀ᵐ (y : γ) ∂Measure.map f μ, p y

Tactic:
]

Goal state after:
α : Type u_1
β : Type u_2
γ : Type u_3
inst✝² : MeasurableSpace α
inst✝¹ : MeasurableSpace β
inst✝ : MeasurableSpace γ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
h : IdentDistrib f g μ ν
p : γ → Prop
pmeas : MeasurableSet {x | p x}
hp : ∀ᵐ (x : α) ∂μ, p (f x)
⊢ ∀ᵐ (y : γ) ∂Measure.map f μ, p y
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: E : Type u_3
F : Type u_4
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
mE : MeasurableSpace E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace ℝ F
mF : MeasurableSpace F
μ : Measure E
inst✝¹ : IsProbabilityMeasure μ
ν : Measure F
inst✝ : IsProbabilityMeasure ν
L : StrongDual ℝ (E × F)
hLμ : MemLp (⇑(L ∘SL ContinuousLinearMap.inl ℝ E F)) 2 μ
hLν : MemLp (⇑(L ∘SL ContinuousLinearMap.inr ℝ E F)) 2 ν
this : ⇑L = fun x ↦ (L ∘SL ContinuousLinearMap.inl ℝ E F) x.1 + (L ∘SL ContinuousLinearMap.inr ℝ E F) x.2
⊢ Var[⇑(L ∘SL ContinuousLinearMap.inl ℝ E F); μ] + Var[⇑(L ∘SL ContinuousLinearMap.inr ℝ E F); ν] =
    Var[⇑(L ∘SL ContinuousLinearMap.inl ℝ E F); μ] + Var[⇑(L ∘SL ContinuousLinearMap.inr ℝ E F); ν]

Tactic:
]

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
inst✝¹ : MeasurableSpace α
inst✝ : MeasurableSpace β
μ : Measure α
ν : Measure β
f : α → ℝ≥0∞
g : β → ℝ≥0∞
h : IdentDistrib f g μ ν
⊢ ∫⁻ (a : ℝ≥0∞), id a ∂Measure.map g ν = ∫⁻ (a : ℝ≥0∞), id a ∂Measure.map g ν

Tactic:
]

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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
⊢ AEMeasurable id (Measure.map f μ) ∧ ∃ t, IsSeparable t ∧ ∀ᵐ (x : γ) ∂Measure.map f μ, id x ∈ t

Tactic:
]

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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
⊢ AEMeasurable id (Measure.map f μ) ∧ ∃ t, IsSeparable t ∧ ∀ᵐ (x : γ) ∂Measure.map f μ, id x ∈ t
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
t : Set γ
t_sep : IsSeparable t
ht : ∀ᵐ (x : α) ∂μ, f x ∈ t
⊢ ∀ᵐ (x : α) ∂μ, id (f x) ∈ closure[PseudoMetricSpace.toUniformSpace.toTopologicalSpace] t

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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
t : Set γ
t_sep : IsSeparable t
ht : ∀ᵐ (x : α) ∂μ, f x ∈ t
⊢ MeasurableSet {x | id x ∈ closure[PseudoMetricSpace.toUniformSpace.toTopologicalSpace] t}

Tactic:
]

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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
t : Set γ
t_sep : IsSeparable t
ht : ∀ᵐ (x : α) ∂μ, f x ∈ t
⊢ ∀ᵐ (x : α) ∂μ, id (f x) ∈ closure[PseudoMetricSpace.toUniformSpace.toTopologicalSpace] t

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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
t : Set γ
t_sep : IsSeparable t
ht : ∀ᵐ (x : α) ∂μ, f x ∈ t
⊢ MeasurableSet {x | id x ∈ closure[PseudoMetricSpace.toUniformSpace.toTopologicalSpace] t}
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
Ω : ι → Type u_5
m : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝⁶ : ∀ (i : ι), IsProbabilityMeasure (μ i)
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 : TopologicalSpace E
inst✝² : HasOuterApproxClosed E
inst✝¹ : BorelSpace E
X : (i : ι) → Ω i → E
Z : Ω' → E
W : Ω'' → E
inst✝ : l.NeBot
h1 : TendstoInDistribution X l Z μ μ'
h2 : TendstoInDistribution X l W μ μ''
h_eq : ↑⟨Measure.map Z μ', ⋯⟩ = ↑⟨Measure.map W μ'', ⋯⟩
⊢ Measure.map Z μ' = Measure.map W μ''

Tactic:
]

Goal state after:
ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
Ω : ι → Type u_5
m : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝⁶ : ∀ (i : ι), IsProbabilityMeasure (μ i)
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 : TopologicalSpace E
inst✝² : HasOuterApproxClosed E
inst✝¹ : BorelSpace E
X : (i : ι) → Ω i → E
Z : Ω' → E
W : Ω'' → E
inst✝ : l.NeBot
h1 : TendstoInDistribution X l Z μ μ'
h2 : TendstoInDistribution X l W μ μ''
h_eq : ↑⟨Measure.map Z μ', ⋯⟩ = ↑⟨Measure.map W μ'', ⋯⟩
⊢ Measure.map Z μ' = Measure.map W μ''
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: case e_a
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 : ι → Type u_8
m : (i : ι) → MeasurableSpace (β i)
f : (i : ι) → Ω → β i
S T : Finset ι
hST : Disjoint S T
hf_meas : ∀ (i : ι), Measurable (f i)
hμ : μ ≠ 0
η : Kernel α Ω
η_eq : ⇑κ =ᵐ[μ] ⇑η
hη : IsMarkovKernel η
πSβ : Set (Set ((i : ↥S) → β ↑i)) := univ.pi '' univ.pi fun i ↦ {s | MeasurableSet s}
πS : Set (Set Ω) := {s | ∃ t ∈ πSβ, (fun a i ↦ f (↑i) a) ⁻¹' t = s}
hπS_pi : IsPiSystem πS
hπS_gen : MeasurableSpace.comap (fun a i ↦ f (↑i) a) MeasurableSpace.pi = generateFrom πS
πTβ : Set (Set ((i : ↥T) → β ↑i)) := univ.pi '' univ.pi fun i ↦ {s | MeasurableSet s}
πT : Set (Set Ω) := {s | ∃ t ∈ πTβ, (fun a i ↦ f (↑i) a) ⁻¹' t = s}
hπT_pi : IsPiSystem πT
hπT_gen : MeasurableSpace.comap (fun a i ↦ f (↑i) a) MeasurableSpace.pi = generateFrom πT
s : Set ((i : ↥S) → β ↑i)
sets_s : (i : ↥S) → Set (β ↑i)
hs2 : univ.pi sets_s = s
t : Set ((i : ↥T) → β ↑i)
sets_t : (i : ↥T) → Set (β ↑i)
ht2 : univ.pi sets_t = t
hs1 : ∀ (i : ↥S), MeasurableSet (sets_s i)
ht1 : ∀ (i : ↥T), MeasurableSet (sets_t i)
sets_s' : (i : ι) → Set (β i) := fun i ↦ if hi : i ∈ S then sets_s ⟨i, hi⟩ else univ
h_sets_s'_eq : ∀ {i : ι} (hi : i ∈ S), sets_s' i = sets_s ⟨i, hi⟩
h_sets_s'_univ : ∀ {i : ι}, i ∈ T → sets_s' i = univ
sets_t' : (i : ι) → Set (β i) := fun i ↦ if hi : i ∈ T then sets_t ⟨i, hi⟩ else univ
h_sets_t'_univ : ∀ {i : ι}, i ∈ S → sets_t' i = univ
h_meas_s' : ∀ i ∈ S, MeasurableSet (sets_s' i)
h_meas_t' : ∀ i ∈ T, MeasurableSet (sets_t' i)
h_eq_inter_S : (fun ω i ↦ f (↑i) ω) ⁻¹' univ.pi sets_s = ⋂ i ∈ S, f i ⁻¹' sets_s' i
h_eq_inter_T : (fun ω i ↦ f (↑i) ω) ⁻¹' univ.pi sets_t = ⋂ i ∈ T, f i ⁻¹' sets_t' i
hf_Indep :
  ∀ (S : Finset ι) {sets : (i : ι) → Set (β i)},
    (∀ i ∈ S, MeasurableSet (sets i)) → ∀ᵐ (a : α) ∂μ, (η a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (η a) (f i ⁻¹' sets i)
h_Inter_inter : (⋂ i ∈ S, f i ⁻¹' sets_s' i) ∩ ⋂ i ∈ T, f i ⁻¹' sets_t' i = ⋂ i ∈ S ∪ T, f i ⁻¹' (sets_s' i ∩ sets_t' i)
h_meas_inter : ∀ i ∈ S ∪ T, MeasurableSet (sets_s' i ∩ sets_t' i)
a : α
h_indepS : (η a) (⋂ i ∈ S, f i ⁻¹' sets_s' i) = ∏ i ∈ S, (η a) (f i ⁻¹' sets_s' i)
h_indepT : (η a) (⋂ i ∈ T, f i ⁻¹' sets_t' i) = ∏ i ∈ T, (η a) (f i ⁻¹' sets_t' i)
h_indepST : (η a) (⋂ i ∈ S ∪ T, f i ⁻¹' (sets_s' i ∩ sets_t' i)) = ∏ i ∈ S ∪ T, (η a) (f i ⁻¹' (sets_s' i ∩ sets_t' i))
i : ι
hi : i ∈ S
⊢ (η a) (f i ⁻¹' sets_s' i) = (η a) (f i ⁻¹' sets_s' i)

Tactic:
]

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

Goal state before:
pp: case e'_3
ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω : ι → Type u_5
m : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝⁶ : ∀ (i : ι), IsProbabilityMeasure (μ i)
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
mE : MeasurableSpace E
X : (i : ι) → Ω i → E
Z : Ω' → E
l : Filter ι
inst✝⁴ : TopologicalSpace E
F : Type u_6
inst✝³ : OpensMeasurableSpace E
inst✝² : TopologicalSpace F
inst✝¹ : MeasurableSpace F
inst✝ : BorelSpace F
g : E → F
hg : Continuous[inst✝⁴, inst✝²] g
h : TendstoInDistribution X l Z μ μ'
x✝ : ι
⊢ Measure.map (g ∘ X x✝) (μ x✝) = Measure.map (g ∘ X x✝) (μ x✝)

Tactic:
]

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: case pos
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
A : AEStronglyMeasurable id (Measure.map f μ)
⊢ ∫ (y : γ), id y ∂Measure.map f μ = ∫ (x : β), id (g x) ∂ν

Tactic:
]

Goal state after:
case pos
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
A : AEStronglyMeasurable id (Measure.map f μ)
⊢ ∫ (y : γ), id y ∂Measure.map f μ = ∫ (x : β), id (g x) ∂ν
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: case pos
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
A : AEStronglyMeasurable id (Measure.map g ν)
⊢ ∫ (y : γ), id y ∂Measure.map f μ = ∫ (x : β), id (g x) ∂ν

Tactic:
]

Goal state after:
case pos
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
A : AEStronglyMeasurable id (Measure.map g ν)
⊢ ∫ (y : γ), id y ∂Measure.map f μ = ∫ (x : β), id (g x) ∂ν
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: case pos
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : AEStronglyMeasurable f μ
A : AEStronglyMeasurable id (Measure.map g ν)
⊢ ∫ (y : γ), id y ∂Measure.map g ν = ∫ (y : γ), id y ∂Measure.map g ν

Tactic:
]

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
β : Type u_3
β' : Type u_4
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
f : Ω → β
g : Ω → β'
hfm : Measurable f
hgm : Measurable g
⊢ (∀ {φ : β → ℝ} {ψ : β' → ℝ},
      Measurable φ →
        Measurable ψ →
          Integrable (φ ∘ f) μ →
            Integrable (ψ ∘ g) μ → integral μ (φ ∘ f * ψ ∘ g) = integral μ (φ ∘ f) * integral μ (ψ ∘ g)) →
    ∀ (t1 t2 : Set Ω), MeasurableSet t1 → MeasurableSet t2 → μ (t1 ∩ t2) = μ t1 * μ t2

Tactic:
]

Goal state after:
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
β : Type u_3
β' : Type u_4
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
f : Ω → β
g : Ω → β'
hfm : Measurable f
hgm : Measurable g
⊢ (∀ {φ : β → ℝ} {ψ : β' → ℝ},
      Measurable φ →
        Measurable ψ →
          Integrable (φ ∘ f) μ →
            Integrable (ψ ∘ g) μ → integral μ (φ ∘ f * ψ ∘ g) = integral μ (φ ∘ f) * integral μ (ψ ∘ g)) →
    ∀ (t1 t2 : Set Ω), MeasurableSet t1 → MeasurableSet t2 → μ (t1 ∩ t2) = μ t1 * μ t2
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: case neg
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : ¬AEStronglyMeasurable f μ
⊢ 0 = ∫ (x : β), g x ∂ν

Tactic:
]

Goal state after:
case neg
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : ¬AEStronglyMeasurable f μ
⊢ 0 = ∫ (x : β), g x ∂ν
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: case neg
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : ¬AEStronglyMeasurable g ν
⊢ 0 = ∫ (x : β), g x ∂ν

Tactic:
]

Goal state after:
case neg
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : ¬AEStronglyMeasurable g ν
⊢ 0 = ∫ (x : β), g x ∂ν
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: case neg
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 : NormedAddCommGroup γ
inst✝¹ : NormedSpace ℝ γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : ¬AEStronglyMeasurable g ν
⊢ 0 = 0

Tactic:
]

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

Goal state before:
pp: case e'_5
ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω : ι → Type u_5
m : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝⁶ : ∀ (i : ι), IsProbabilityMeasure (μ i)
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
mE : MeasurableSpace E
X : (i : ι) → Ω i → E
Z : Ω' → E
l : Filter ι
inst✝⁴ : TopologicalSpace E
F : Type u_6
inst✝³ : OpensMeasurableSpace E
inst✝² : TopologicalSpace F
inst✝¹ : MeasurableSpace F
inst✝ : BorelSpace F
g : E → F
hg : Continuous[inst✝⁴, inst✝²] g
h : TendstoInDistribution X l Z μ μ'
⊢ Measure.map (g ∘ Z) μ' = Measure.map (g ∘ Z) μ'

Tactic:
]

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: 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✝ : BorelSpace γ
p : ℝ≥0∞
h : IdentDistrib f g μ ν
hf : MemLp f p μ
⊢ eLpNorm f p μ < ∞

Tactic:
]

Goal state after:
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✝ : BorelSpace γ
p : ℝ≥0∞
h : IdentDistrib f g μ ν
hf : MemLp f p μ
⊢ eLpNorm f p μ < ∞
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: 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✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : MemLp f 1 μ
⊢ MemLp g 1 ν

Tactic:
]

Goal state after:
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✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : MemLp f 1 μ
⊢ MemLp g 1 ν
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: case e'_3
α : Type u_1
β : Type u_2
inst✝¹ : MeasurableSpace α
inst✝ : MeasurableSpace β
μ : Measure α
ν : Measure β
f : α → ℝ
g : β → ℝ
h : IdentDistrib f g μ ν
⊢ eVar[g; ν] = ∫⁻ (x : β), ↑‖g x - ∫ (x : β), g x ∂ν‖₊ ^ 2 ∂ν

Tactic:
]

Goal state after:
case e'_3
α : Type u_1
β : Type u_2
inst✝¹ : MeasurableSpace α
inst✝ : MeasurableSpace β
μ : Measure α
ν : Measure β
f : α → ℝ
g : β → ℝ
h : IdentDistrib f g μ ν
⊢ eVar[g; ν] = ∫⁻ (x : β), ↑‖g x - ∫ (x : β), g x ∂ν‖₊ ^ 2 ∂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
⊢ Tendsto (fun i ↦ ∫⁻ (ω : E), ↑(f ω) ∂Measure.map (X i) μ') l (𝓝 (∫⁻ (ω : E), ↑(f ω) ∂Measure.map Z μ'))

Tactic:
lintegral_map' (by fun_prop) hZ

Goal state after:
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
⊢ Tendsto (fun i ↦ ∫⁻ (ω : E), ↑(f ω) ∂Measure.map (X i) μ') l (𝓝 (∫⁻ (a : Ω'), ↑(f (Z a)) ∂μ'))
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
⊢ Tendsto (fun i ↦ ∫⁻ (ω : E), ↑(f ω) ∂Measure.map (X i) μ') l (𝓝 (∫⁻ (a : Ω'), ↑(f (Z a)) ∂μ'))

Tactic:
]

Goal state after:
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
⊢ Tendsto (fun i ↦ ∫⁻ (ω : E), ↑(f ω) ∂Measure.map (X i) μ') l (𝓝 (∫⁻ (a : Ω'), ↑(f (Z a)) ∂μ'))
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
inst✝¹ : MeasurableSpace α
inst✝ : MeasurableSpace β
μ : Measure α
ν : Measure β
f : α → ℝ
g : β → ℝ
h : IdentDistrib f g μ ν
⊢ eVar[g; ν].toReal = Var[g; ν]

Tactic:
]

Goal state after:
α : Type u_1
β : Type u_2
inst✝¹ : MeasurableSpace α
inst✝ : MeasurableSpace β
μ : Measure α
ν : Measure β
f : α → ℝ
g : β → ℝ
h : IdentDistrib f g μ ν
⊢ eVar[g; ν].toReal = Var[g; ν]