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

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
X : ι → Ω → α
Y : ι → Ω → β
f : ι → Set Ω
t : ι → Set β
s : Finset ι
inst✝ : Finite ι
hY : ∀ (i : ι), Measurable (Y i)
hindep : iIndepFun (fun i ω ↦ (X i ω, Y i ω)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy✝ : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
val✝ : Fintype ι
g : ι → Set Ω := fun i' ↦ if i' ∈ s then Y i' ⁻¹' t i' ∩ f i' else Y i' ⁻¹' t i'
hYt✝ : ∀ (i : ι), MeasurableSet (Y i ⁻¹' t i)
hg✝ : ∀ (i : ι), MeasurableSet (g i)
a : α
hy : ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
a✝ : IsProbabilityMeasure (κ a)
hYt : (κ a) (⋂ i, Y i ⁻¹' t i) = ∏ i, (κ a) (Y i ⁻¹' t i)
hg : (κ a) (⋂ i, g i) = ∏ i, (κ a) (g i)
⊢ ((κ a) (⋂ i, Y i ⁻¹' t i))⁻¹ * (κ a) ((⋂ i, Y i ⁻¹' t i) ∩ ⋂ i ∈ s, f i) =
    ((κ a) (⋂ i, Y i ⁻¹' t i))⁻¹ * (κ a) (⋂ i, g i)

Tactic:
by

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

Goal state before:
pp: α : Type u_2
inst✝¹ : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
r : ℝ≥0∞
s : ℕ → Set α
hs : ∀ (n : ℕ), MeasurableSet (s n)
hr₀ : r ≠ 0
hr : ∀ (n : ℕ), r ≤ μ (s n)
M : (α → ℝ) → Set α := fun f ↦ {x | eLpNormEssSup f μ < ↑‖f x‖₊}
N : Set α := ⋃ u, M ((⋂ n ∈ u, s n).indicator 1)
hN₀ : μ N = 0
hN₁ : ∀ (u : Finset ℕ), ((⋂ n ∈ u, s n) \ N).Nonempty → 0 < μ (⋂ n ∈ u, s n)
f : ℕ → α → ℝ≥0∞ := fun n ↦ (↑(n + 1))⁻¹ • ∑ k ∈ Finset.range (n + 1), (s k).indicator 1
hfapp : ∀ (n : ℕ) (a : α), f n a = (↑(n + 1))⁻¹ * ∑ k ∈ Finset.range (n + 1), (s k).indicator 1 a
hf : ∀ (n : ℕ), Measurable (f n)
hf₁ : ∀ (n : ℕ), f n ≤ 1
n : ℕ
⊢ r ≤ ∫⁻ (a : α), f n a ∂μ

Tactic:
by

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

Goal state before:
pp: α : Type u_2
inst✝¹ : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
r : ℝ≥0∞
s : ℕ → Set α
hs : ∀ (n : ℕ), MeasurableSet (s n)
hr₀ : r ≠ 0
hr : ∀ (n : ℕ), r ≤ μ (s n)
M : (α → ℝ) → Set α := fun f ↦ {x | eLpNormEssSup f μ < ↑‖f x‖₊}
N : Set α := ⋃ u, M ((⋂ n ∈ u, s n).indicator 1)
hN₀ : μ N = 0
hN₁ : ∀ (u : Finset ℕ), ((⋂ n ∈ u, s n) \ N).Nonempty → 0 < μ (⋂ n ∈ u, s n)
f : ℕ → α → ℝ≥0∞ := fun n ↦ (↑(n + 1))⁻¹ • ∑ k ∈ Finset.range (n + 1), (s k).indicator 1
hfapp : ∀ (n : ℕ) (a : α), f n a = (↑(n + 1))⁻¹ * ∑ k ∈ Finset.range (n + 1), (s k).indicator 1 a
hf : ∀ (n : ℕ), Measurable (f n)
hf₁ : ∀ (n : ℕ), f n ≤ 1
hrf : ∀ (n : ℕ), r ≤ ∫⁻ (a : α), f n a ∂μ
⊢ μ ≠ 0

Tactic:
by

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
h_le :
  ∀ (n : ι),
    |∫ (ω : E), F ω ∂Measure.map (Y n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'| ≤
      ↑L * (ε / 2) + M * μ''.real {ω | ε / 2 ≤ ‖Y n ω - X n ω‖} +
        |∫ (ω : E), F ω ∂Measure.map (X n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'|
⊢ Tendsto
    (fun n ↦
      ↑L * (ε / 2) + M * μ''.real {ω | ε / 2 ≤ ‖Y n ω - X n ω‖} +
        |∫ (ω : E), F ω ∂Measure.map (X n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'|)
    l (𝓝 (↑L * ε / 2))

Tactic:
by

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
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
X : ι → Ω → α
Y : ι → Ω → β
f : ι → Set Ω
t : ι → Set β
s : Finset ι
inst✝ : Finite ι
hY : ∀ (i : ι), Measurable (Y i)
hindep : iIndepFun (fun i ω ↦ (X i ω, Y i ω)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy✝ : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
val✝ : Fintype ι
g : ι → Set Ω := fun i' ↦ if i' ∈ s then Y i' ⁻¹' t i' ∩ f i' else Y i' ⁻¹' t i'
hYt✝ : ∀ (i : ι), MeasurableSet (Y i ⁻¹' t i)
hg✝ : ∀ (i : ι), MeasurableSet (g i)
a : α
hy : ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
a✝ : IsProbabilityMeasure (κ a)
hYt : (κ a) (⋂ i, Y i ⁻¹' t i) = ∏ i, (κ a) (Y i ⁻¹' t i)
hg : (κ a) (⋂ i, g i) = ∏ i, (κ a) (g i)
⊢ ((κ a) (⋂ i, Y i ⁻¹' t i))⁻¹ * (κ a) (⋂ i, g i) = (∏ i, (κ a) (Y i ⁻¹' t i))⁻¹ * (κ a) (⋂ i, g i)

Tactic:
by

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
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
X : ι → Ω → α
Y : ι → Ω → β
f : ι → Set Ω
t : ι → Set β
s : Finset ι
inst✝ : Finite ι
hY : ∀ (i : ι), Measurable (Y i)
hindep : iIndepFun (fun i ω ↦ (X i ω, Y i ω)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy✝ : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
val✝ : Fintype ι
g : ι → Set Ω := fun i' ↦ if i' ∈ s then Y i' ⁻¹' t i' ∩ f i' else Y i' ⁻¹' t i'
hYt✝ : ∀ (i : ι), MeasurableSet (Y i ⁻¹' t i)
hg✝ : ∀ (i : ι), MeasurableSet (g i)
a : α
hy : ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
a✝ : IsProbabilityMeasure (κ a)
hYt : (κ a) (⋂ i, Y i ⁻¹' t i) = ∏ i, (κ a) (Y i ⁻¹' t i)
hg : (κ a) (⋂ i, g i) = ∏ i, (κ a) (g i)
⊢ (∏ i, (κ a) (Y i ⁻¹' t i))⁻¹ * (κ a) (⋂ i, g i) = (∏ i, (κ a) (Y i ⁻¹' t i))⁻¹ * ∏ i, (κ a) (g i)

Tactic:
by

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

Goal state before:
pp: α : Type u_2
inst✝¹ : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
r : ℝ≥0∞
s : ℕ → Set α
hs : ∀ (n : ℕ), MeasurableSet (s n)
hr₀ : r ≠ 0
hr : ∀ (n : ℕ), r ≤ μ (s n)
M : (α → ℝ) → Set α := fun f ↦ {x | eLpNormEssSup f μ < ↑‖f x‖₊}
N : Set α := ⋃ u, M ((⋂ n ∈ u, s n).indicator 1)
hN₀ : μ N = 0
hN₁ : ∀ (u : Finset ℕ), ((⋂ n ∈ u, s n) \ N).Nonempty → 0 < μ (⋂ n ∈ u, s n)
f : ℕ → α → ℝ≥0∞ := fun n ↦ (↑(n + 1))⁻¹ • ∑ k ∈ Finset.range (n + 1), (s k).indicator 1
hfapp : ∀ (n : ℕ) (a : α), f n a = (↑(n + 1))⁻¹ * ∑ k ∈ Finset.range (n + 1), (s k).indicator 1 a
hf : ∀ (n : ℕ), Measurable (f n)
hf₁ : ∀ (n : ℕ), f n ≤ 1
hrf : ∀ (n : ℕ), r ≤ ∫⁻ (a : α), f n a ∂μ
hμ : μ ≠ 0
⊢ ∫⁻ (x : α), limsup (fun x_1 ↦ f x_1 x) atTop ∂μ ≤ μ univ

Tactic:
by

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
h_le :
  ∀ (n : ι),
    |∫ (ω : E), F ω ∂Measure.map (Y n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'| ≤
      ↑L * (ε / 2) + M * μ''.real {ω | ε / 2 ≤ ‖Y n ω - X n ω‖} +
        |∫ (ω : E), F ω ∂Measure.map (X n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'|
h_tendsto :
  Tendsto
    (fun n ↦
      ↑L * (ε / 2) + M * μ''.real {ω | ε / 2 ≤ ‖Y n ω - X n ω‖} +
        |∫ (ω : E), F ω ∂Measure.map (X n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'|)
    l (𝓝 (↑L * ε / 2))
⊢ 0 < ↑L * ε

Tactic:
by

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
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
X : ι → Ω → α
Y : ι → Ω → β
f : ι → Set Ω
t : ι → Set β
s : Finset ι
inst✝ : Finite ι
hY : ∀ (i : ι), Measurable (Y i)
hindep : iIndepFun (fun i ω ↦ (X i ω, Y i ω)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy✝ : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
val✝ : Fintype ι
g : ι → Set Ω := fun i' ↦ if i' ∈ s then Y i' ⁻¹' t i' ∩ f i' else Y i' ⁻¹' t i'
hYt✝ : ∀ (i : ι), MeasurableSet (Y i ⁻¹' t i)
hg✝ : ∀ (i : ι), MeasurableSet (g i)
a : α
hy : ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
a✝ : IsProbabilityMeasure (κ a)
hYt : (κ a) (⋂ i, Y i ⁻¹' t i) = ∏ i, (κ a) (Y i ⁻¹' t i)
hg : (κ a) (⋂ i, g i) = ∏ i, (κ a) (g i)
⊢ (∏ i, (κ a) (Y i ⁻¹' t i))⁻¹ * ∏ i, (κ a) (g i) = ∏ i, ((κ a) (Y i ⁻¹' t i))⁻¹ * (κ a) (g i)

Tactic:
by

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''
⊢ TendstoInDistribution Y l Z (fun x ↦ μ'') μ'

Tactic:
by

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 : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
inst✝ : l.IsCountablyGenerated
X : ι → Ω' → E
h : TendstoInMeasure μ' X l Z
hX : ∀ (i : ι), AEMeasurable (X i) μ'
hZ : AEMeasurable Z μ'
⊢ TendstoInMeasure μ' (X - fun x ↦ Z) l 0

Tactic:
by

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

Goal state before:
pp: α : Type u_2
inst✝¹ : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
r : ℝ≥0∞
s : ℕ → Set α
hs : ∀ (n : ℕ), MeasurableSet (s n)
hr₀ : r ≠ 0
hr : ∀ (n : ℕ), r ≤ μ (s n)
M : (α → ℝ) → Set α := fun f ↦ {x | eLpNormEssSup f μ < ↑‖f x‖₊}
N : Set α := ⋃ u, M ((⋂ n ∈ u, s n).indicator 1)
hN₀ : μ N = 0
hN₁ : ∀ (u : Finset ℕ), ((⋂ n ∈ u, s n) \ N).Nonempty → 0 < μ (⋂ n ∈ u, s n)
f : ℕ → α → ℝ≥0∞ := fun n ↦ (↑(n + 1))⁻¹ • ∑ k ∈ Finset.range (n + 1), (s k).indicator 1
hfapp : ∀ (n : ℕ) (a : α), f n a = (↑(n + 1))⁻¹ * ∑ k ∈ Finset.range (n + 1), (s k).indicator 1 a
hf : ∀ (n : ℕ), Measurable (f n)
hf₁ : ∀ (n : ℕ), f n ≤ 1
hrf : ∀ (n : ℕ), r ≤ ∫⁻ (a : α), f n a ∂μ
hμ : μ ≠ 0
this : ∫⁻ (x : α), limsup (fun x_1 ↦ f x_1 x) atTop ∂μ ≤ μ univ
⊢ μ univ ≠ ∞

Tactic:
by

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✝⁸ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁷ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝⁶ : SeminormedAddCommGroup E
inst✝⁵ : SecondCountableTopology E
inst✝⁴ : BorelSpace E
E' : Type u_6
mE' : MeasurableSpace E'
inst✝³ : SeminormedAddCommGroup E'
inst✝² : SecondCountableTopology E'
inst✝¹ : BorelSpace E'
inst✝ : l.IsCountablyGenerated
X : ι → Ω'' → E
Y : ι → Ω'' → E'
Z : Ω' → E
c : E'
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hY : TendstoInMeasure μ'' Y l fun x ↦ c
hY_meas : ∀ (i : ι), AEMeasurable (Y i) μ''
hX : ∀ (i : ι), AEMeasurable (X i) μ''
⊢ Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, PseudoMetricSpace.toUniformSpace.toTopologicalSpace]
    fun x ↦ (x, c)

Tactic:
by

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✝⁸ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁷ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝⁶ : SeminormedAddCommGroup E
inst✝⁵ : SecondCountableTopology E
inst✝⁴ : BorelSpace E
E' : Type u_6
mE' : MeasurableSpace E'
inst✝³ : SeminormedAddCommGroup E'
inst✝² : SecondCountableTopology E'
inst✝¹ : BorelSpace E'
inst✝ : l.IsCountablyGenerated
X : ι → Ω'' → E
Y : ι → Ω'' → E'
Z : Ω' → E
c : E'
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hY : TendstoInMeasure μ'' Y l fun x ↦ c
hY_meas : ∀ (i : ι), AEMeasurable (Y i) μ''
hX : ∀ (i : ι), AEMeasurable (X i) μ''
this : TendstoInMeasure μ'' (fun n ω ↦ (0, Y n ω - c)) l 0
⊢ TendstoInMeasure μ'' ((fun n ω ↦ (X n ω, Y n ω)) - fun n ω ↦ (X n ω, c)) l 0

Tactic:
by

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✝⁸ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁷ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝⁶ : SeminormedAddCommGroup E
inst✝⁵ : SecondCountableTopology E
inst✝⁴ : BorelSpace E
E' : Type u_6
mE' : MeasurableSpace E'
inst✝³ : SeminormedAddCommGroup E'
inst✝² : SecondCountableTopology E'
inst✝¹ : BorelSpace E'
inst✝ : l.IsCountablyGenerated
X : ι → Ω'' → E
Y : ι → Ω'' → E'
Z : Ω' → E
c : E'
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hY : TendstoInMeasure μ'' Y l fun x ↦ c
hY_meas : ∀ (i : ι), AEMeasurable (Y i) μ''
⊢ TendstoInDistribution (fun n ω ↦ (X n ω, Y n ω)) l (fun ω ↦ (Z ω, c)) (fun x ↦ μ'') μ'

Tactic:
by

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
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
X : ι → Ω → α
Y : ι → Ω → β
f : ι → Set Ω
t : ι → Set β
s : Finset ι
inst✝ : Finite ι
hY : ∀ (i : ι), Measurable (Y i)
hindep : iIndepFun (fun i ω ↦ (X i ω, Y i ω)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy✝ : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
val✝ : Fintype ι
g : ι → Set Ω := fun i' ↦ if i' ∈ s then Y i' ⁻¹' t i' ∩ f i' else Y i' ⁻¹' t i'
hYt✝ : ∀ (i : ι), MeasurableSet (Y i ⁻¹' t i)
hg✝ : ∀ (i : ι), MeasurableSet (g i)
a : α
hy : ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
a✝ : IsProbabilityMeasure (κ a)
hYt : (κ a) (⋂ i, Y i ⁻¹' t i) = ∏ i, (κ a) (Y i ⁻¹' t i)
hg : (κ a) (⋂ i, g i) = ∏ i, (κ a) (g i)
⊢ ∏ i, ((κ a) (Y i ⁻¹' t i))⁻¹ * (κ a) (g i) = ∏ i, if i ∈ s then (κ a)[f i | Y i ⁻¹' t i] else 1

Tactic:
by

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

Goal state before:
pp: α : Type u_2
inst✝¹ : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
r : ℝ≥0∞
s : ℕ → Set α
hs : ∀ (n : ℕ), MeasurableSet (s n)
hr₀ : r ≠ 0
hr : ∀ (n : ℕ), r ≤ μ (s n)
M : (α → ℝ) → Set α := fun f ↦ {x | eLpNormEssSup f μ < ↑‖f x‖₊}
N : Set α := ⋃ u, M ((⋂ n ∈ u, s n).indicator 1)
hN₀ : μ N = 0
hN₁ : ∀ (u : Finset ℕ), ((⋂ n ∈ u, s n) \ N).Nonempty → 0 < μ (⋂ n ∈ u, s n)
f : ℕ → α → ℝ≥0∞ := fun n ↦ (↑(n + 1))⁻¹ • ∑ k ∈ Finset.range (n + 1), (s k).indicator 1
hfapp : ∀ (n : ℕ) (a : α), f n a = (↑(n + 1))⁻¹ * ∑ k ∈ Finset.range (n + 1), (s k).indicator 1 a
hf : ∀ (n : ℕ), Measurable (f n)
hf₁ : ∀ (n : ℕ), f n ≤ 1
hrf : ∀ (n : ℕ), r ≤ ∫⁻ (a : α), f n a ∂μ
hμ : μ ≠ 0
this : ∫⁻ (x : α), limsup (fun x_1 ↦ f x_1 x) atTop ∂μ ≤ μ univ
x : α
hxN : x ∉ N
hx : ⨍⁻ (a : α), limsup (fun x ↦ f x a) atTop ∂μ ≤ limsup (fun x_1 ↦ f x_1 x) atTop
⊢ ∫⁻ (a : α), 1 a ∂(μ univ)⁻¹ • μ ≠ ∞

Tactic:
by

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✝¹¹ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝¹⁰ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
Z : Ω' → E
l : Filter ι
inst✝⁹ : SeminormedAddCommGroup E
inst✝⁸ : SecondCountableTopology E
inst✝⁷ : BorelSpace E
E' : Type u_6
F : Type u_7
mE' : MeasurableSpace E'
inst✝⁶ : SeminormedAddCommGroup E'
inst✝⁵ : SecondCountableTopology E'
inst✝⁴ : BorelSpace E'
inst✝³ : TopologicalSpace F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
g : E × E' → F
hg : Continuous[instTopologicalSpaceProd, inst✝³] g
inst✝ : l.IsCountablyGenerated
X : ι → Ω'' → E
Y : ι → Ω'' → E'
c : E'
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hY_tendsto : TendstoInMeasure μ'' Y l fun x ↦ c
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
⊢ TendstoInDistribution (fun n ω ↦ g (X n ω, Y n ω)) l (fun ω ↦ g (Z ω, c)) (fun x ↦ μ'') μ'

Tactic:
by

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
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
X : ι → Ω → α
Y : ι → Ω → β
f : ι → Set Ω
t : ι → Set β
s : Finset ι
inst✝ : Finite ι
hY : ∀ (i : ι), Measurable (Y i)
hindep : iIndepFun (fun i ω ↦ (X i ω, Y i ω)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy✝ : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
val✝ : Fintype ι
g : ι → Set Ω := fun i' ↦ if i' ∈ s then Y i' ⁻¹' t i' ∩ f i' else Y i' ⁻¹' t i'
hYt✝ : ∀ (i : ι), MeasurableSet (Y i ⁻¹' t i)
hg✝ : ∀ (i : ι), MeasurableSet (g i)
a : α
hy : ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
a✝ : IsProbabilityMeasure (κ a)
hYt : (κ a) (⋂ i, Y i ⁻¹' t i) = ∏ i, (κ a) (Y i ⁻¹' t i)
hg : (κ a) (⋂ i, g i) = ∏ i, (κ a) (g i)
⊢ (∏ i, if i ∈ s then (κ a)[f i | Y i ⁻¹' t i] else 1) = ∏ i ∈ s, (κ a)[f i | Y i ⁻¹' t i]

Tactic:
by

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
Z : Ω' → E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X Y : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
c : E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hY_tendsto : TendstoInMeasure μ'' Y l fun x ↦ c
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
⊢ Continuous[instTopologicalSpaceProd, PseudoMetricSpace.toUniformSpace.toTopologicalSpace] fun x ↦ x.1 + x.2

Tactic:
by

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
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
X : ι → Ω → α
Y : ι → Ω → β
f : ι → Set Ω
t : ι → Set β
s : Finset ι
inst✝ : Finite ι
hY : ∀ (i : ι), Measurable (Y i)
hindep : iIndepFun (fun i ω ↦ (X i ω, Y i ω)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
⊢ ∀ᵐ (a : α) ∂μ, (κ a)[⋂ i ∈ s, f i | ⋂ i, Y i ⁻¹' t i] = ∏ i ∈ s, (κ a)[f i | Y i ⁻¹' t i]

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSeminorm.Count

Goal state before:
pp: α : Type u_1
ε : Type u_2
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSingletonClass α
inst✝¹ : TopologicalSpace ε
inst✝ : ContinuousENorm ε
p : ℝ≥0∞
f : α → ε
i : α
hp : p ≠ 0
⊢ eLpNorm f p (dirac i) = ‖f i‖ₑ

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSeminorm.Count

Goal state before:
pp: α : Type u_1
ε : Type u_2
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSingletonClass α
inst✝¹ : TopologicalSpace ε
inst✝ : ContinuousENorm ε
p : ℝ≥0∞
f : α → ε
i : α
hp : p ≠ 0
⊢ ‖f i‖ₑ = eLpNorm f p (dirac i)

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSeminorm.Count

Goal state before:
pp: α : Type u_1
ε : Type u_2
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSingletonClass α
inst✝¹ : TopologicalSpace ε
inst✝ : ContinuousENorm ε
p : ℝ≥0∞
f : α → ε
i : α
hp : p ≠ 0
⊢ eLpNorm f p (dirac i) = eLpNorm f p (count.restrict {i})

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSeminorm.Count

Goal state before:
pp: α : Type u_1
ε : Type u_2
inst✝³ : MeasurableSpace α
inst✝² : MeasurableSingletonClass α
inst✝¹ : TopologicalSpace ε
inst✝ : ContinuousENorm ε
p : ℝ≥0∞
f : α → ε
i : α
hp : p ≠ 0
⊢ ‖f i‖ₑ ≤ eLpNorm f p count

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
ι : Type u_2
m : MeasurableSpace Ω
β : ι → Type u_3
inst✝⁵ : (i : ι) → TopologicalSpace (β i)
inst✝⁴ : ∀ (i : ι), MetrizableSpace (β i)
mβ : (i : ι) → MeasurableSpace (β i)
inst✝³ : ∀ (i : ι), BorelSpace (β i)
inst✝² : Preorder ι
inst✝¹ : (i : ι) → MulZeroOneClass (β i)
inst✝ : ∀ (i : ι), Nontrivial (β i)
s : ι → Set Ω
hsm : ∀ (i : ι), MeasurableSet (s i)
⊢ filtrationOfSet hsm = natural (fun i ↦ (s i).indicator fun x ↦ 1) ⋯

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSeminorm.Count

Goal state before:
pp: α : Type u_1
ε : Type u_2
inst✝³ : MeasurableSpace α
inst✝² : TopologicalSpace ε
inst✝¹ : ContinuousENorm ε
f : α → ε
p : ℝ≥0∞
inst✝ : Finite α
h : ∀ (i : α), ‖f i‖ₑ < ∞
this : Fintype α
⊢ ‖Finset.univ.sup fun x ↦ ‖f x‖ₑ‖ₑ ≠ ∞

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSeminorm.Count

Goal state before:
pp: α : Type u_1
ε : Type u_2
inst✝³ : MeasurableSpace α
inst✝² : TopologicalSpace ε
inst✝¹ : ContinuousENorm ε
f : α → ε
p : ℝ≥0∞
inst✝ : Finite α
h : ∀ (i : α), ‖f i‖ₑ < ∞
⊢ eLpNorm f p count < ∞

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
ι : Type u_2
m : MeasurableSpace Ω
inst✝² : Preorder ι
E : Type u_4
inst✝¹ : Zero E
inst✝ : TopologicalSpace E
ℱ : Filtration ι m
f : ι → Ω → E
μ : Measure Ω
⊢ StronglyMeasurable (limitProcess f ℱ μ)

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSpace.DomAct.Basic

Goal state before:
pp: M : Type u_1
N : Type u_2
α : Type u_3
E : Type u_4
inst✝⁴ : MeasurableSpace α
inst✝³ : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝² : SMul M α
inst✝¹ : SMulInvariantMeasure M α μ
inst✝ : MeasurableConstSMul M α
c : M
s : Set α
hs : MeasurableSet s
hμs : μ s ≠ ∞
b : E
⊢ μ ((fun x ↦ c • x) ⁻¹' s) ≠ ∞

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSpace.DomAct.Basic

Goal state before:
pp: M : Type u_1
α : Type u_3
E : Type u_4
inst✝⁴ : MeasurableSpace α
inst✝³ : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝² : SMul M α
inst✝¹ : SMulInvariantMeasure M α μ
inst✝ : MeasurableConstSMul M α
c : Mᵈᵐᵃ
⊢ ∀ (f g : ↥(Lp E p μ)), c • (f + g) = c • f + c • g

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSpace.DomAct.Basic

Goal state before:
pp: M : Type u_1
α : Type u_3
E : Type u_4
inst✝⁴ : MeasurableSpace α
inst✝³ : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝² : SMul M α
inst✝¹ : SMulInvariantMeasure M α μ
inst✝ : MeasurableConstSMul M α
c : Mᵈᵐᵃ
f : ↥(Lp E p μ)
⊢ c • -f = -(c • f)

Tactic:
by

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSpace.ContinuousCompMeasurePreserving

Goal state before:
pp: X : Type u_1
Y : Type u_2
inst✝¹¹ : TopologicalSpace X
inst✝¹⁰ : MeasurableSpace X
inst✝⁹ : BorelSpace X
inst✝⁸ : R1Space X
inst✝⁷ : TopologicalSpace Y
inst✝⁶ : MeasurableSpace Y
inst✝⁵ : BorelSpace Y
inst✝⁴ : R1Space Y
μ : Measure X
ν : Measure Y
inst✝³ : μ.InnerRegularCompactLTTop
inst✝² : IsLocallyFiniteMeasure ν
E : Type u_3
inst✝¹ : NormedAddCommGroup E
p : ℝ≥0∞
inst✝ : Fact (1 ≤ p)
hp : p ≠ ∞
⊢ Continuous[instTopologicalSpaceProd, PseudoMetricSpace.toUniformSpace.toTopologicalSpace] fun gf ↦
    (compMeasurePreserving ⇑↑gf.2 ⋯) gf.1

Tactic:
by

Goal state after: