mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.MeasureTheory.Function.UniformIntegrable

Goal state before:
pp: case e_f
α : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace α
μ : Measure α
inst✝ : NormedAddCommGroup β
p : ℝ≥0∞
hp : 1 ≤ p
hp' : p ≠ ∞
f : ι → α → β
hf : ∀ (i : ι), StronglyMeasurable (f i)
h : ∀ (ε : ℝ), 0 < ε → ∃ C, 0 < C ∧ ∀ (i : ι), eLpNorm ({x | C ≤ ‖f i x‖₊}.indicator (f i)) p μ ≤ ENNReal.ofReal ε
hpzero : p ≠ 0
hμ : ¬μ univ = 0
ε : ℝ
hε : 0 < ε
C : ℝ≥0
hCpos : 0 < C
hC : ∀ (i : ι), eLpNorm ({x | C ≤ ‖f i x‖₊}.indicator (f i)) p μ ≤ ENNReal.ofReal (ε / 2)
i : ι
s : Set α
hs : MeasurableSet s
hμs : μ s ≤ ENNReal.ofReal ((ε / (2 * ↑C)) ^ p.toReal)
hμs' : ¬μ s = 0
⊢ s.indicator (f i) = fun x ↦ (s ∩ {x | C ≤ ‖f i x‖₊}).indicator (f i) x + (s ∩ {x | ‖f i x‖₊ < C}).indicator (f i) x

Tactic:
← Set.indicator_union_of_disjoint

Goal state after:
case e_f
α : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace α
μ : Measure α
inst✝ : NormedAddCommGroup β
p : ℝ≥0∞
hp : 1 ≤ p
hp' : p ≠ ∞
f : ι → α → β
hf : ∀ (i : ι), StronglyMeasurable (f i)
h : ∀ (ε : ℝ), 0 < ε → ∃ C, 0 < C ∧ ∀ (i : ι), eLpNorm ({x | C ≤ ‖f i x‖₊}.indicator (f i)) p μ ≤ ENNReal.ofReal ε
hpzero : p ≠ 0
hμ : ¬μ univ = 0
ε : ℝ
hε : 0 < ε
C : ℝ≥0
hCpos : 0 < C
hC : ∀ (i : ι), eLpNorm ({x | C ≤ ‖f i x‖₊}.indicator (f i)) p μ ≤ ENNReal.ofReal (ε / 2)
i : ι
s : Set α
hs : MeasurableSet s
hμs : μ s ≤ ENNReal.ofReal ((ε / (2 * ↑C)) ^ p.toReal)
hμs' : ¬μ s = 0
⊢ s.indicator (f i) = (s ∩ {x | C ≤ ‖f i x‖₊} ∪ s ∩ {x | ‖f i x‖₊ < C}).indicator (f i)

case e_f.h
α : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace α
μ : Measure α
inst✝ : NormedAddCommGroup β
p : ℝ≥0∞
hp : 1 ≤ p
hp' : p ≠ ∞
f : ι → α → β
hf : ∀ (i : ι), StronglyMeasurable (f i)
h : ∀ (ε : ℝ), 0 < ε → ∃ C, 0 < C ∧ ∀ (i : ι), eLpNorm ({x | C ≤ ‖f i x‖₊}.indicator (f i)) p μ ≤ ENNReal.ofReal ε
hpzero : p ≠ 0
hμ : ¬μ univ = 0
ε : ℝ
hε : 0 < ε
C : ℝ≥0
hCpos : 0 < C
hC : ∀ (i : ι), eLpNorm ({x | C ≤ ‖f i x‖₊}.indicator (f i)) p μ ≤ ENNReal.ofReal (ε / 2)
i : ι
s : Set α
hs : MeasurableSet s
hμs : μ s ≤ ENNReal.ofReal ((ε / (2 * ↑C)) ^ p.toReal)
hμs' : ¬μ s = 0
⊢ Disjoint (s ∩ {x | C ≤ ‖f i x‖₊}) (s ∩ {x | ‖f i x‖₊ < C})
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
ι : Type u_2
inst✝ : IsFiniteMeasure μ
g : α → ℝ
hint : Integrable g μ
ℱ : ι → MeasurableSpace α
hℱ : ∀ (i : ι), ℱ i ≤ m0
A : MeasurableSpace α := m0
hmeas : ∀ (n : ι) (C : ℝ≥0), MeasurableSet {x | C ≤ ‖μ[g | ℱ n] x‖₊}
hg : MemLp g 1 μ
ε : ℝ
hε : 0 < ε
hne : ¬eLpNorm g 1 μ = 0
δ : ℝ
hδ : 0 < δ
h : ∀ (s : Set α), MeasurableSet s → μ s ≤ ENNReal.ofReal δ → eLpNorm (s.indicator g) 1 μ ≤ ENNReal.ofReal ε
C : ℝ≥0 := (NNReal.mk δ ⋯)⁻¹ * (eLpNorm g 1 μ).toNNReal
hC : C = (NNReal.mk δ ⋯)⁻¹ * (eLpNorm g 1 μ).toNNReal
hCpos : 0 < C
n : ι
⊢ ↑C ^ ENNReal.toReal 1 * μ {x | ↑C ≤ ↑‖μ[g | ℱ n] x‖₊} ≤ eLpNorm μ[g | ℱ n] 1 μ ^ ENNReal.toReal 1

Tactic:
rw [ENNReal.toReal_one, ENNReal.rpow_one]

Goal state after:
α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
ι : Type u_2
inst✝ : IsFiniteMeasure μ
g : α → ℝ
hint : Integrable g μ
ℱ : ι → MeasurableSpace α
hℱ : ∀ (i : ι), ℱ i ≤ m0
A : MeasurableSpace α := m0
hmeas : ∀ (n : ι) (C : ℝ≥0), MeasurableSet {x | C ≤ ‖μ[g | ℱ n] x‖₊}
hg : MemLp g 1 μ
ε : ℝ
hε : 0 < ε
hne : ¬eLpNorm g 1 μ = 0
δ : ℝ
hδ : 0 < δ
h : ∀ (s : Set α), MeasurableSet s → μ s ≤ ENNReal.ofReal δ → eLpNorm (s.indicator g) 1 μ ≤ ENNReal.ofReal ε
C : ℝ≥0 := (NNReal.mk δ ⋯)⁻¹ * (eLpNorm g 1 μ).toNNReal
hC : C = (NNReal.mk δ ⋯)⁻¹ * (eLpNorm g 1 μ).toNNReal
hCpos : 0 < C
n : ι
⊢ ↑C * μ {x | ↑C ≤ ↑‖μ[g | ℱ n] x‖₊} ≤ eLpNorm μ[g | ℱ n] 1 μ ^ 1
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
ι : Type u_2
inst✝ : IsFiniteMeasure μ
g : α → ℝ
hint : Integrable g μ
ℱ : ι → MeasurableSpace α
hℱ : ∀ (i : ι), ℱ i ≤ m0
A : MeasurableSpace α := m0
hmeas : ∀ (n : ι) (C : ℝ≥0), MeasurableSet {x | C ≤ ‖μ[g | ℱ n] x‖₊}
hg : MemLp g 1 μ
ε : ℝ
hε : 0 < ε
hne : ¬eLpNorm g 1 μ = 0
δ : ℝ
hδ : 0 < δ
h : ∀ (s : Set α), MeasurableSet s → μ s ≤ ENNReal.ofReal δ → eLpNorm (s.indicator g) 1 μ ≤ ENNReal.ofReal ε
C : ℝ≥0 := (NNReal.mk δ ⋯)⁻¹ * (eLpNorm g 1 μ).toNNReal
hC : C = (NNReal.mk δ ⋯)⁻¹ * (eLpNorm g 1 μ).toNNReal
hCpos : 0 < C
n : ι
this : μ {x | C ≤ ‖μ[g | ℱ n] x‖₊} ≤ eLpNorm μ[g | ℱ n] 1 μ ^ 1 / ↑C
⊢ eLpNorm μ[g | ℱ n] 1 μ ^ 1 ≤ ENNReal.ofReal δ * (↑(NNReal.mk δ⁻¹ ⋯) * eLpNorm g 1 μ)

Tactic:
← mul_assoc,

Goal state after:
α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
ι : Type u_2
inst✝ : IsFiniteMeasure μ
g : α → ℝ
hint : Integrable g μ
ℱ : ι → MeasurableSpace α
hℱ : ∀ (i : ι), ℱ i ≤ m0
A : MeasurableSpace α := m0
hmeas : ∀ (n : ι) (C : ℝ≥0), MeasurableSet {x | C ≤ ‖μ[g | ℱ n] x‖₊}
hg : MemLp g 1 μ
ε : ℝ
hε : 0 < ε
hne : ¬eLpNorm g 1 μ = 0
δ : ℝ
hδ : 0 < δ
h : ∀ (s : Set α), MeasurableSet s → μ s ≤ ENNReal.ofReal δ → eLpNorm (s.indicator g) 1 μ ≤ ENNReal.ofReal ε
C : ℝ≥0 := (NNReal.mk δ ⋯)⁻¹ * (eLpNorm g 1 μ).toNNReal
hC : C = (NNReal.mk δ ⋯)⁻¹ * (eLpNorm g 1 μ).toNNReal
hCpos : 0 < C
n : ι
this : μ {x | C ≤ ‖μ[g | ℱ n] x‖₊} ≤ eLpNorm μ[g | ℱ n] 1 μ ^ 1 / ↑C
⊢ eLpNorm μ[g | ℱ n] 1 μ ^ 1 ≤ ENNReal.ofReal δ * ↑(NNReal.mk δ⁻¹ ⋯) * eLpNorm g 1 μ
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: case inr
Ω : Type u_1
inst✝² : MeasurableSpace Ω
ι : Type u_2
L : Filter ι
μ : Measure Ω
μs : ι → Measure Ω
inst✝¹ : IsProbabilityMeasure μ
inst✝ : ∀ (i : ι), IsProbabilityMeasure (μs i)
E : Set Ω
E_mble : MeasurableSet E
h : μ E ≤ liminf (fun i ↦ (μs i) E) L
hne : L.NeBot
meas_Ec : μ Eᶜ = 1 - μ E
meas_i_Ec : ∀ (i : ι), (μs i) Eᶜ = 1 - (μs i) E
⊢ limsup (fun i ↦ 1 - (μs i) E) L ≤ 1 - μ E

Tactic:
show (L.limsup fun i : ι ↦ 1 - μs i E) = L.limsup ((fun x ↦ 1 - x) ∘ fun i : ι ↦ μs i E)
      from rfl

Goal state after:
case inr
Ω : Type u_1
inst✝² : MeasurableSpace Ω
ι : Type u_2
L : Filter ι
μ : Measure Ω
μs : ι → Measure Ω
inst✝¹ : IsProbabilityMeasure μ
inst✝ : ∀ (i : ι), IsProbabilityMeasure (μs i)
E : Set Ω
E_mble : MeasurableSet E
h : μ E ≤ liminf (fun i ↦ (μs i) E) L
hne : L.NeBot
meas_Ec : μ Eᶜ = 1 - μ E
meas_i_Ec : ∀ (i : ι), (μs i) Eᶜ = 1 - (μs i) E
⊢ limsup ((fun x ↦ 1 - x) ∘ fun i ↦ (μs i) E) L ≤ 1 - μ E
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ η : Kernel α Ω
μ : Measure α
π : ι → Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝² : Finset ι
a✝¹ : ι → Set Ω
a✝ : ∀ i ∈ a✝², a✝¹ i ∈ π i
h' : ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (κ a) (a✝¹ i)
a : α
ha : κ a = η a
⊢ (κ a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (κ a) (a✝¹ i) → (η a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (η a) (a✝¹ i)

Tactic:
h'a

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ η : Kernel α Ω
μ : Measure α
π : ι → Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝² : Finset ι
a✝¹ : ι → Set Ω
a✝ : ∀ i ∈ a✝², a✝¹ i ∈ π i
h' : ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (κ a) (a✝¹ i)
a : α
ha : κ a = η a
h'a : (κ a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (κ a) (a✝¹ i)
⊢ (η a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (η a) (a✝¹ i)
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ η : Kernel α Ω
μ : Measure α
π : ι → Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝² : Finset ι
a✝¹ : ι → Set Ω
a✝ : ∀ i ∈ a✝², a✝¹ i ∈ π i
h' : ∀ᵐ (a : α) ∂μ, (η a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (η a) (a✝¹ i)
a : α
ha : κ a = η a
⊢ (η a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (η a) (a✝¹ i) → (κ a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (κ a) (a✝¹ i)

Tactic:
h'a

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ η : Kernel α Ω
μ : Measure α
π : ι → Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝² : Finset ι
a✝¹ : ι → Set Ω
a✝ : ∀ i ∈ a✝², a✝¹ i ∈ π i
h' : ∀ᵐ (a : α) ∂μ, (η a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (η a) (a✝¹ i)
a : α
ha : κ a = η a
h'a : (η a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (η a) (a✝¹ i)
⊢ (κ a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (κ a) (a✝¹ i)
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ η : Kernel α Ω
μ : Measure α
s1 s2 : Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝³ a✝² : Set Ω
a✝¹ : a✝³ ∈ s1
a✝ : a✝² ∈ s2
h' : ∀ᵐ (a : α) ∂μ, (κ a) (a✝³ ∩ a✝²) = (κ a) a✝³ * (κ a) a✝²
a : α
ha : κ a = η a
⊢ (κ a) (a✝³ ∩ a✝²) = (κ a) a✝³ * (κ a) a✝² → (η a) (a✝³ ∩ a✝²) = (η a) a✝³ * (η a) a✝²

Tactic:
h'a

Goal state after:
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ η : Kernel α Ω
μ : Measure α
s1 s2 : Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝³ a✝² : Set Ω
a✝¹ : a✝³ ∈ s1
a✝ : a✝² ∈ s2
h' : ∀ᵐ (a : α) ∂μ, (κ a) (a✝³ ∩ a✝²) = (κ a) a✝³ * (κ a) a✝²
a : α
ha : κ a = η a
h'a : (κ a) (a✝³ ∩ a✝²) = (κ a) a✝³ * (κ a) a✝²
⊢ (η a) (a✝³ ∩ a✝²) = (η a) a✝³ * (η a) a✝²
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ η : Kernel α Ω
μ : Measure α
s1 s2 : Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝³ a✝² : Set Ω
a✝¹ : a✝³ ∈ s1
a✝ : a✝² ∈ s2
h' : ∀ᵐ (a : α) ∂μ, (η a) (a✝³ ∩ a✝²) = (η a) a✝³ * (η a) a✝²
a : α
ha : κ a = η a
⊢ (η a) (a✝³ ∩ a✝²) = (η a) a✝³ * (η a) a✝² → (κ a) (a✝³ ∩ a✝²) = (κ a) a✝³ * (κ a) a✝²

Tactic:
h'a

Goal state after:
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ η : Kernel α Ω
μ : Measure α
s1 s2 : Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝³ a✝² : Set Ω
a✝¹ : a✝³ ∈ s1
a✝ : a✝² ∈ s2
h' : ∀ᵐ (a : α) ∂μ, (η a) (a✝³ ∩ a✝²) = (η a) a✝³ * (η a) a✝²
a : α
ha : κ a = η a
h'a : (η a) (a✝³ ∩ a✝²) = (η a) a✝³ * (η a) a✝²
⊢ (κ a) (a✝³ ∩ a✝²) = (κ a) a✝³ * (κ a) a✝²
Module: Mathlib.Probability.Independence.Kernel.Indep

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
π : ι → Set (Set Ω)
s : ι → Set Ω
inst✝ : Fintype ι
h : iIndepSets π κ μ
hs : ∀ (i : ι), s i ∈ π i
a : α
ha : (κ a) (⋂ i ∈ Finset.univ, s i) = ∏ i, (κ a) (s i)
⊢ (κ a) (⋂ i, s i) = ∏ i, (κ a) (s i)

Tactic:
simp [← ha]

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

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
m : ι → MeasurableSpace Ω
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
s : ι → Set Ω
inst✝ : Fintype ι
h : iIndep m κ μ
hs : ∀ (i : ι), MeasurableSet (s i)
a : α
ha : (κ a) (⋂ i ∈ Finset.univ, s i) = ∏ i, (κ a) (s i)
⊢ (κ a) (⋂ i, s i) = ∏ i, (κ a) (s i)

Tactic:
simp [← ha]

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: Ω : Type u_1
inst✝³ : PseudoMetricSpace Ω
inst✝² : MeasurableSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
μ : Measure Ω
inst✝ : SFinite μ
s : Set Ω
Rs : ℕ → ℝ
left✝ : StrictAnti Rs
Rs_pos : ∀ (n : ℕ), 0 < Rs n
Rs_lim : Tendsto Rs atTop (𝓝 0)
⊢ ∃ rs, Tendsto rs atTop (𝓝 0) ∧ ∀ (n : ℕ), 0 < rs n ∧ μ (frontier (Metric.thickening (rs n) s)) = 0

Tactic:
have obs := fun n : ℕ => exists_null_frontier_thickening μ s (Rs_pos n)

Goal state after:
Ω : Type u_1
inst✝³ : PseudoMetricSpace Ω
inst✝² : MeasurableSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
μ : Measure Ω
inst✝ : SFinite μ
s : Set Ω
Rs : ℕ → ℝ
left✝ : StrictAnti Rs
Rs_pos : ∀ (n : ℕ), 0 < Rs n
Rs_lim : Tendsto Rs atTop (𝓝 0)
obs : ∀ (n : ℕ), ∃ r ∈ Ioo 0 (Rs n), μ (frontier (Metric.thickening r s)) = 0
⊢ ∃ rs, Tendsto rs atTop (𝓝 0) ∧ ∀ (n : ℕ), 0 < rs n ∧ μ (frontier (Metric.thickening (rs n) s)) = 0
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 : ι → Type u_8
mβ : (i : ι) → MeasurableSpace (β i)
f g : (i : ι) → Ω → β i
hf :
  ∀ (S : Finset ι) {sets : (i : ι) → Set (β i)},
    (∀ i ∈ S, MeasurableSet (sets i)) → ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i)
h : ∀ (i : ι), ∀ᵐ (a : α) ∂μ, f i =ᵐ[κ a] g i
S : Finset ι
sets : (i : ι) → Set (β i)
hmeas : ∀ i ∈ S, MeasurableSet (sets i)
this : ∀ᵐ (a : α) ∂μ, ∀ i ∈ S, f i =ᵐ[κ a] g i
a : α
ha : ∀ i ∈ S, f i =ᵐ[κ a] g i
⊢ (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i) →
    (κ a) (⋂ i ∈ S, g i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (g i ⁻¹' sets i)

Tactic:
h'a

Goal state after:
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
mβ : (i : ι) → MeasurableSpace (β i)
f g : (i : ι) → Ω → β i
hf :
  ∀ (S : Finset ι) {sets : (i : ι) → Set (β i)},
    (∀ i ∈ S, MeasurableSet (sets i)) → ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i)
h : ∀ (i : ι), ∀ᵐ (a : α) ∂μ, f i =ᵐ[κ a] g i
S : Finset ι
sets : (i : ι) → Set (β i)
hmeas : ∀ i ∈ S, MeasurableSet (sets i)
this : ∀ᵐ (a : α) ∂μ, ∀ i ∈ S, f i =ᵐ[κ a] g i
a : α
ha : ∀ i ∈ S, f i =ᵐ[κ a] g i
h'a : (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i)
⊢ (κ a) (⋂ i ∈ S, g i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (g i ⁻¹' sets i)
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: case h
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m₂ m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h2 : m₂ ≤ m
hp2 : IsPiSystem p2
hpm2 : m₂ = generateFrom p2
hyp : IndepSets p1 p2 κ μ
t1 t2 : Set Ω
ht1 : t1 ∈ p1
ht1m : MeasurableSet t1
h : IsMarkovKernel κ
f : ℕ → Set Ω
hfd : Pairwise (Function.onFun Disjoint f)
hfm : ∀ (i : ℕ), MeasurableSet (f i)
ihf : ∀ᵐ (a : α) ∂μ, ∀ (i : ℕ), (κ a) (t1 ∩ f i) = (κ a) t1 * (κ a) (f i)
a : α
ha : ∀ (i : ℕ), (κ a) (t1 ∩ f i) = (κ a) t1 * (κ a) (f i)
⊢ ∀ (i : ℕ), MeasurableSet (t1 ∩ f i)

Tactic:
exact fun i ↦ .inter ht1m (h2 _ <| hfm i)

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

Goal state before:
pp: α : Type u_1
Ω : Type u_2
β : Type u_4
β' : Type u_5
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
f' : Ω → β
g' : Ω → β'
hfg : IndepFun f g κ μ
hf : ∀ᵐ (a : α) ∂μ, f =ᵐ[κ a] f'
hg : ∀ᵐ (a : α) ∂μ, g =ᵐ[κ a] g'
A : Set β
hA : MeasurableSet A
B : Set β'
hB : MeasurableSet B
a : α
hf' : f =ᵐ[κ a] f'
hg' : g =ᵐ[κ a] g'
hfg' : (κ a) (f ⁻¹' A ∩ g ⁻¹' B) = (κ a) (f ⁻¹' A) * (κ a) (g ⁻¹' B)
⊢ (κ a) (f' ⁻¹' A ∩ g' ⁻¹' B) = (κ a) (f' ⁻¹' A) * (κ a) (g' ⁻¹' B)

Tactic:
have h1 : f ⁻¹' A =ᵐ[κ a] f' ⁻¹' A := hf'.fun_comp (· ∈ A)

Goal state after:
α : Type u_1
Ω : Type u_2
β : Type u_4
β' : Type u_5
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
f' : Ω → β
g' : Ω → β'
hfg : IndepFun f g κ μ
hf : ∀ᵐ (a : α) ∂μ, f =ᵐ[κ a] f'
hg : ∀ᵐ (a : α) ∂μ, g =ᵐ[κ a] g'
A : Set β
hA : MeasurableSet A
B : Set β'
hB : MeasurableSet B
a : α
hf' : f =ᵐ[κ a] f'
hg' : g =ᵐ[κ a] g'
hfg' : (κ a) (f ⁻¹' A ∩ g ⁻¹' B) = (κ a) (f ⁻¹' A) * (κ a) (g ⁻¹' B)
h1 : f ⁻¹' A =ᵐ[κ a] f' ⁻¹' A
⊢ (κ a) (f' ⁻¹' A ∩ g' ⁻¹' B) = (κ a) (f' ⁻¹' A) * (κ a) (g' ⁻¹' B)
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: case h
Ω : Type u_1
ι : Type u_2
mΩ : MeasurableSpace Ω
inst✝² : TopologicalSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
μ : ProbabilityMeasure Ω
μs : ι → ProbabilityMeasure Ω
L : Filter ι
inst✝ : L.IsCountablyGenerated
h₁ : IsTightMeasureSet (range (ProbabilityMeasure.toMeasure ∘ μs))
h₂ : ∀ (F : Set Ω), IsCompact F → limsup (fun x ↦ (μs x) F) L ≤ μ F
h✝ : L.NeBot
F : Set Ω
hF_closed : IsClosed[inst✝²] F
ε : ℝ≥0
hε : 0 < ε
x✝ : ↑(μ F) < ∞
K : Set Ω
hKc : IsCompact K
hK_le : ∀ μ ∈ range (ProbabilityMeasure.toMeasure ∘ μs), μ Kᶜ ≤ ↑ε
i : ι
⊢ ↑(μs i) F ≤ ↑(μs i) (F ∩ K) + ↑ε

Tactic:
measure_mono (t := (F ∩ K) ∪ F \ K) (by simp),

Goal state after:
case h
Ω : Type u_1
ι : Type u_2
mΩ : MeasurableSpace Ω
inst✝² : TopologicalSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
μ : ProbabilityMeasure Ω
μs : ι → ProbabilityMeasure Ω
L : Filter ι
inst✝ : L.IsCountablyGenerated
h₁ : IsTightMeasureSet (range (ProbabilityMeasure.toMeasure ∘ μs))
h₂ : ∀ (F : Set Ω), IsCompact F → limsup (fun x ↦ (μs x) F) L ≤ μ F
h✝ : L.NeBot
F : Set Ω
hF_closed : IsClosed[inst✝²] F
ε : ℝ≥0
hε : 0 < ε
x✝ : ↑(μ F) < ∞
K : Set Ω
hKc : IsCompact K
hK_le : ∀ μ ∈ range (ProbabilityMeasure.toMeasure ∘ μs), μ Kᶜ ≤ ↑ε
i : ι
⊢ ↑(μs i) (F ∩ K ∪ F \ K) ≤ ↑(μs i) (F ∩ K) + ↑ε
Module: Mathlib.Probability.Density

Goal state before:
pp: Ω : Type u_1
E : Type u_2
inst✝² : MeasurableSpace E
m : MeasurableSpace Ω
ℙ : Measure Ω
μ : Measure E
F : Type u_3
inst✝¹ : MeasurableSpace F
ν : Measure F
X : Ω → E
inst✝ : HasPDF X ℙ μ
g : E → F
hg : QuasiMeasurePreserving g μ ν
hmap : (map g (map X ℙ)).HaveLebesgueDecomposition ν
hgm : AEMeasurable g (map X ℙ)
⊢ HasPDF (g ∘ X) ℙ ν

Tactic:
hasPDF_iff,

Goal state after:
Ω : Type u_1
E : Type u_2
inst✝² : MeasurableSpace E
m : MeasurableSpace Ω
ℙ : Measure Ω
μ : Measure E
F : Type u_3
inst✝¹ : MeasurableSpace F
ν : Measure F
X : Ω → E
inst✝ : HasPDF X ℙ μ
g : E → F
hg : QuasiMeasurePreserving g μ ν
hmap : (map g (map X ℙ)).HaveLebesgueDecomposition ν
hgm : AEMeasurable g (map X ℙ)
⊢ AEMeasurable (g ∘ X) ℙ ∧ (map (g ∘ X) ℙ).HaveLebesgueDecomposition ν ∧ map (g ∘ X) ℙ ≪ ν
Module: Mathlib.Probability.Density

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → ℝ
inst✝ : SFinite ℙ
⊢ HasPDF X ℙ volume ↔ AEMeasurable X ℙ ∧ map X ℙ ≪ volume

Tactic:
hasPDF_iff,

Goal state after:
Ω : Type u_1
m : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → ℝ
inst✝ : SFinite ℙ
⊢ AEMeasurable X ℙ ∧ (map X ℙ).HaveLebesgueDecomposition volume ∧ map X ℙ ≪ volume ↔ AEMeasurable X ℙ ∧ map X ℙ ≪ volume
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X Y : Ω → ℝ
μ : Measure Ω
h : X =ᵐ[μ] Y
⊢ Var[X; μ] = Var[Y; μ]

Tactic:
simp_rw [variance, evariance_congr h]

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X Y : Ω → ℝ
μ : Measure Ω
c : ℝ
⊢ ∫ (ω : Ω), (c * X ω - ∫ (x : Ω), c * X x ∂μ) * (Y ω - ∫ (x : Ω), Y x ∂μ) ∂μ =
    ∫ (a : Ω), c * ((X a - ∫ (x : Ω), X x ∂μ) * (Y a - ∫ (x : Ω), Y x ∂μ)) ∂μ

Tactic:
← mul_assoc,

Goal state after:
Ω : Type u_1
mΩ : MeasurableSpace Ω
X Y : Ω → ℝ
μ : Measure Ω
c : ℝ
⊢ ∫ (ω : Ω), (c * X ω - ∫ (x : Ω), c * X x ∂μ) * (Y ω - ∫ (x : Ω), Y x ∂μ) ∂μ =
    ∫ (a : Ω), c * (X a - ∫ (x : Ω), X x ∂μ) * (Y a - ∫ (x : Ω), Y x ∂μ) ∂μ
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: case pos
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_3
X : ι → Ω → ℝ
s : Finset ι
hs : ∀ i ∈ s, MemLp (X i) 2 μ
h : (↑s).Pairwise fun i j ↦ X i ⟂ᵢ[μ] X j
h'' : ∀ i ∈ s, X i =ᵐ[μ] 0
⊢ Var[∑ i ∈ s, X i; μ] = ∑ i ∈ s, Var[X i; μ]

Tactic:
rw [variance_congr (Y := 0), variance_zero]

Goal state after:
case pos
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_3
X : ι → Ω → ℝ
s : Finset ι
hs : ∀ i ∈ s, MemLp (X i) 2 μ
h : (↑s).Pairwise fun i j ↦ X i ⟂ᵢ[μ] X j
h'' : ∀ i ∈ s, X i =ᵐ[μ] 0
⊢ 0 = ∑ i ∈ s, Var[X i; μ]

case pos
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_3
X : ι → Ω → ℝ
s : Finset ι
hs : ∀ i ∈ s, MemLp (X i) 2 μ
h : (↑s).Pairwise fun i j ↦ X i ⟂ᵢ[μ] X j
h'' : ∀ i ∈ s, X i =ᵐ[μ] 0
⊢ ∑ i ∈ s, X i =ᵐ[μ] 0
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 : Integrable f μ
⊢ Integrable g ν

Tactic:
← memLp_one_iff_integrable

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.Independence.Integration

Goal state before:
pp: case e_f
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)
ω : Ω
⊢ A.indicator (fun ω ↦ f (X ω)) ω = id (A.indicator 1 ω) • f (X ω)

Tactic:
by_cases hω : ω ∈ A <;> simp [hω]

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

Goal state before:
pp: case refine_3.refine_1
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 : r / μ univ ≤ limsup (fun x_1 ↦ f x_1 x) atTop
hxs : {n | x ∈ s n}.Finite
⊢ False

Tactic:
refine ENNReal.div_ne_zero.2 ⟨hr₀, by finiteness⟩ <| eq_bot_mono hx <|
        Tendsto.limsup_eq <| tendsto_of_tendsto_of_tendsto_of_le_of_le tendsto_const_nhds
        (h := fun n ↦ (n.succ : ℝ≥0∞)⁻¹ * hxs.toFinset.card) ?_ bot_le fun n ↦ mul_le_mul_right ?_ _
      · simpa using ENNReal.Tendsto.mul_const (ENNReal.tendsto_inv_nat_nhds_zero.comp <|
          tendsto_add_atTop_nat 1) (.inr <| ENNReal.natCast_ne_top _)
      · classical
        simpa only [Finset.sum_apply, indicator_apply, Pi.one_apply, Finset.sum_boole, Nat.cast_le]
          using! Finset.card_le_card fun m hm ↦ hxs.mem_toFinset.2 (Finset.mem_filter.1 hm).2

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

Goal state before:
pp: case neg.refine_2
ι : Type u_1
α : Type u_2
β : Type u_3
inst✝² : MeasurableSpace α
s : ι → Set α
f : ι → α → β
inst✝¹ : Countable ι
hs : IndexedPartition s
hm : ∀ (i : ι), MeasurableSet (s i)
inst✝ : TopologicalSpace β
hf : ∀ (i : ι), StronglyMeasurable (f i)
Fi : Infinite ι
e : ℕ ≃ ι
g : (n : ℕ) → ι → Fin (n + 1) := fun n i ↦ if hi : ∃ m < n, i = e m then ⟨hi.choose, ⋯⟩ else Fin.last n
sg : ∀ (n : ℕ), Function.Surjective (g n)
G : (n : ℕ) → IndexedPartition fun k ↦ ⋃ i ∈ g n ⁻¹' {k}, s i
x : α
this : ∀ᶠ (n : ℕ) in atTop, e ↑((G n).index x) = hs.index x
⊢ Tendsto (fun n ↦ (⋯.approx n) x) atTop (nhds (f (hs.index x) x))

Tactic:
have : ∀ᶠ n in atTop, (hf (hs.index x)).approx n x = (hf (e ((G n).index x))).approx n x := by
    filter_upwards [this] with n hn using by rw [hn]

Goal state after:
case neg.refine_2
ι : Type u_1
α : Type u_2
β : Type u_3
inst✝² : MeasurableSpace α
s : ι → Set α
f : ι → α → β
inst✝¹ : Countable ι
hs : IndexedPartition s
hm : ∀ (i : ι), MeasurableSet (s i)
inst✝ : TopologicalSpace β
hf : ∀ (i : ι), StronglyMeasurable (f i)
Fi : Infinite ι
e : ℕ ≃ ι
g : (n : ℕ) → ι → Fin (n + 1) := fun n i ↦ if hi : ∃ m < n, i = e m then ⟨hi.choose, ⋯⟩ else Fin.last n
sg : ∀ (n : ℕ), Function.Surjective (g n)
G : (n : ℕ) → IndexedPartition fun k ↦ ⋃ i ∈ g n ⁻¹' {k}, s i
x : α
this✝ : ∀ᶠ (n : ℕ) in atTop, e ↑((G n).index x) = hs.index x
this : ∀ᶠ (n : ℕ) in atTop, (⋯.approx n) x = (⋯.approx n) x
⊢ Tendsto (fun n ↦ (⋯.approx n) x) atTop (nhds (f (hs.index x) x))
Module: Mathlib.MeasureTheory.Group.FoelnerFilter

Goal state before:
pp: G : Type u_1
X : Type u_2
inst✝³ : MeasurableSpace X
μ : Measure X
inst✝² : Group G
inst✝¹ : MulAction G X
ι : Type u_3
u : Ultrafilter ι
F : ι → Set X
inst✝ : SMulInvariantMeasure G X μ
hfoel : IsFoelner G μ (↑u) F
g : G
s : Set X
⊢ mean μ u F (g • s) = mean μ u F s

Tactic:
simpa using hfoel.mean_smul_eq_mean_smul g 1 s

Goal state after: