Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: case refine_2
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 ↦ μ''.real {ω | ε / 2 ≤ ‖Y n ω - X n ω‖}) l (𝓝 0)

pp: case refine_3
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 ↦ |∫ (ω : E), F ω ∂Measure.map (X n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'|) l (𝓝 0)

Tactic:
·

Goal state after:
case refine_2
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 ↦ μ''.real {ω | ε / 2 ≤ ‖Y n ω - X n ω‖}) l (𝓝 0)