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

Goal state before:
pp: case pos
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
⊢ eLpNorm (s.indicator (f i)) p μ ≤ ENNReal.ofReal ε

Tactic:
(eLpNorm_eq_zero_iff ((hf i).indicator hs).aestronglyMeasurable hpzero).2
        (indicator_meas_zero hμs')

Goal state after:
case pos
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
⊢ 0 ≤ ENNReal.ofReal ε
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
f : α → ℝ
hf : 0 ≤ᵐ[μ] f
⊢ μ[f | m] =ᵐ[μ] fun a ↦ |μ[f | m] a|

Tactic:
filter_upwards [condExp_nonneg hf] with ω hω using (abs_of_nonneg hω).symm

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : CompleteSpace E
p : ℝ
hp : 1 ≤ p
f : α → E
hf : Integrable (fun x ↦ ‖f x‖ ^ p) μ
a : α
⊢ 0 a ≤ ‖μ[f | m] a‖ ^ p

Tactic:
by positivity

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : CompleteSpace E
p : ℝ
hp : 1 ≤ p
f : α → E
hf : Integrable (fun x ↦ ‖f x‖ ^ p) μ
ω : α
⊢ 0 ω ≤ ‖f ω‖ ^ p

Tactic:
by positivity

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

Goal state before:
pp: Ω : Type u_1
inst✝ : MeasurableSpace Ω
μ : FiniteMeasure Ω
s₁ s₂ : Set Ω
⊢ μ (s₁ ∪ s₂) ≤ μ s₁ + μ s₂

Tactic:
have := measure_union_le (μ := (μ : Measure Ω)) s₁ s₂
  apply (ENNReal.toNNReal_mono (by finiteness) this).trans_eq
  rw [ENNReal.toNNReal_add (by finiteness) (by finiteness), coeFn_def]

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : CompleteSpace E
p : ℝ
hp : 1 ≤ p
f : α → E
s : Set α
hs : MeasurableSet s
hf : Integrable (fun x ↦ ‖f x‖ ^ p) μ
hp' : p ≠ 0
hm : ¬m ≤ m0
x : α
⊢ 0 x ≤ ‖f x‖ ^ p

Tactic:
by positivity

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : CompleteSpace E
p : ℝ
hp : 1 ≤ p
f : α → E
s : Set α
hs : MeasurableSet s
hf : Integrable (fun x ↦ ‖f x‖ ^ p) μ
hp' : p ≠ 0
hm : m ≤ m0
hsig : ¬SigmaFinite (μ.trim hm)
x : α
⊢ 0 x ≤ ‖f x‖ ^ p

Tactic:
by positivity

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : CompleteSpace E
p : ℝ
hp : 1 ≤ p
f : α → E
s : Set α
hs : MeasurableSet s
hf : Integrable (fun x ↦ ‖f x‖ ^ p) μ
hp' : p ≠ 0
hm : m ≤ m0
hsig : SigmaFinite (μ.trim hm)
a : α
⊢ 0 a ≤ ‖μ[f | m] a‖ ^ p

Tactic:
by positivity

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : CompleteSpace E
p : ℝ
hp : 1 ≤ p
f : α → E
s : Set α
hs : MeasurableSet s
hf : Integrable (fun x ↦ ‖f x‖ ^ p) μ
hp' : p ≠ 0
hm : m ≤ m0
hsig : SigmaFinite (μ.trim hm)
ω : α
⊢ 0 ω ≤ ‖f ω‖ ^ p

Tactic:
by positivity

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

Goal state before:
pp: case pos
α : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace α
μ : Measure α
inst✝¹ : NormedAddCommGroup β
p : ℝ≥0∞
f : ι → α → β
inst✝ : Finite ι
hp_one : 1 ≤ p
hp_top : p ≠ ∞
hf : ∀ (i : ι), MemLp (f i) p μ
val✝ : Fintype ι
hι : Nonempty ι
⊢ ∃ C, ∀ (i : ι), eLpNorm (f i) p μ ≤ ↑C

Tactic:
choose _ hf using hf
    set C := (Finset.univ.image fun i : ι => eLpNorm (f i) p μ).max'
      ⟨eLpNorm (f hι.some) p μ, Finset.mem_image.2 ⟨hι.some, Finset.mem_univ _, rfl⟩⟩
    refine ⟨C.toNNReal, fun i => ?_⟩
    rw [ENNReal.coe_toNNReal]
    · exact Finset.le_max' (α := ℝ≥0∞) _ _ (Finset.mem_image.2 ⟨i, Finset.mem_univ _, rfl⟩)
    · refine ne_of_lt ((Finset.max'_lt_iff _ _).2 fun y hy => ?_)
      rw [Finset.mem_image] at hy
      obtain ⟨i, -, rfl⟩ := hy
      exact hf i

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

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ : Measure α
p : ℝ≥0∞
E : Type u_4
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℝ E
hp : 1 ≤ p
f : ℕ → α → E
hf₁ : ∀ (i : ℕ), AEStronglyMeasurable (f i) μ
hf₂ : UnifIntegrable f p μ
hf₃ : ∃ C, ∀ (i : ℕ), eLpNorm (f i) p μ ≤ ↑C
ε : ℝ
hε : 0 < ε
δ : ℝ
hδ₁ : 0 < δ
hδ₂ :
  ∀ (i : ℕ) (s : Set α), MeasurableSet s → μ s ≤ ENNReal.ofReal δ → eLpNorm (s.indicator (f i)) p μ ≤ ENNReal.ofReal ε
n : ℕ
s : Set α
hs : MeasurableSet s
hle : μ s ≤ ENNReal.ofReal δ
this : ∀ (i : ℕ), s.indicator ((↑n)⁻¹ • f i) = (↑n)⁻¹ • s.indicator (f i)
hn : n ≠ 0
⊢ ↑n ≠ 0

Tactic:
by positivity

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

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ : Measure α
p : ℝ≥0∞
E : Type u_4
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℝ E
hp : 1 ≤ p
f : ℕ → α → E
hf₁ : ∀ (i : ℕ), AEStronglyMeasurable (f i) μ
hf₂ : UnifIntegrable f p μ
C : ℝ≥0
hC : ∀ (i : ℕ), eLpNorm (f i) p μ ≤ ↑C
n : ℕ
hn : n ≠ 0
⊢ ↑n ≠ 0

Tactic:
by positivity

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

Goal state before:
pp: Ω : Type u_1
β : Type u_6
β' : Type u_7
_mΩ : MeasurableSpace Ω
μ : Measure Ω
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
hf : AEMeasurable f μ
hg : AEMeasurable g μ
σf : SigmaFinite (Measure.map f μ)
σg : SigmaFinite (Measure.map g μ)
⊢ f ⟂ᵢ[μ] g ↔ Measure.map (fun ω ↦ (f ω, g ω)) μ = (Measure.map f μ).prod (Measure.map g μ)

Tactic:
indepFun_iff_measure_inter_preimage_eq_mul

Goal state after:
Ω : Type u_1
β : Type u_6
β' : Type u_7
_mΩ : MeasurableSpace Ω
μ : Measure Ω
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
hf : AEMeasurable f μ
hg : AEMeasurable g μ
σf : SigmaFinite (Measure.map f μ)
σg : SigmaFinite (Measure.map g μ)
⊢ (∀ (s : Set β) (t : Set β'), MeasurableSet s → MeasurableSet t → μ (f ⁻¹' s ∩ g ⁻¹' t) = μ (f ⁻¹' s) * μ (g ⁻¹' t)) ↔
    Measure.map (fun ω ↦ (f ω, g ω)) μ = (Measure.map f μ).prod (Measure.map g μ)
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
μ : ProbabilityMeasure Ω
μs : ℕ → ProbabilityMeasure Ω
h_opens : ∀ (G : Set Ω), IsOpen[inst✝¹] G → μ G ≤ liminf (fun i ↦ (μs i) G) atTop
G : Set Ω
G_open : IsOpen[inst✝¹] G
⊢ ↑μ G ≤ liminf (fun i ↦ ↑(μs i) G) atTop

Tactic:
specialize h_opens G G_open

Goal state after:
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
μ : ProbabilityMeasure Ω
μs : ℕ → ProbabilityMeasure Ω
G : Set Ω
h_opens : μ G ≤ liminf (fun i ↦ (μs i) G) atTop
G_open : IsOpen[inst✝¹] G
⊢ ↑μ G ≤ liminf (fun i ↦ ↑(μs i) G) atTop
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: α : Type u_1
Ω : Type u_2
β : Type u_4
γ : Type u_6
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteKernel κ
f : Ω → β
g : Ω → γ
hf : Measurable f
hg : Measurable g
⊢ IndepFun f g κ μ ↔ (μ ⊗ₘ κ.map fun ω ↦ (f ω, g ω)) = μ ⊗ₘ (κ.map f ×ₖ κ.map g)

Tactic:
indepFun_iff_measure_inter_preimage_eq_mul

Goal state after:
α : Type u_1
Ω : Type u_2
β : Type u_4
γ : Type u_6
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteKernel κ
f : Ω → β
g : Ω → γ
hf : Measurable f
hg : Measurable g
⊢ (∀ (s : Set β) (t : Set γ),
      MeasurableSet s →
        MeasurableSet t → ∀ᵐ (a : α) ∂μ, (κ a) (f ⁻¹' s ∩ g ⁻¹' t) = (κ a) (f ⁻¹' s) * (κ a) (g ⁻¹' t)) ↔
    (μ ⊗ₘ κ.map fun ω ↦ (f ω, g ω)) = μ ⊗ₘ (κ.map f ×ₖ κ.map g)
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: case inr
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
⊢ Tendsto μs L (𝓝 μ)

Tactic:
refine tendsto_of_forall_isClosed_limsup_le <| fun F hF_closed ↦ ?_

Goal state after:
case inr
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
⊢ limsup (fun i ↦ (μs i) F) L ≤ μ F
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: 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) < ∞
⊢ 0 < ↑ε

Tactic:
by positivity

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
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
s : ι → Set (Set Ω)
S T : Set ι
h_indep : iIndepSets s κ μ
hST : Disjoint S T
t1 t2 : Set Ω
p1 : Finset ι
hp1 : ↑p1 ⊆ S
f1 : ι → Set Ω
ht1_m : ∀ x ∈ p1, f1 x ∈ s x
ht1_eq : t1 = ⋂ x ∈ p1, f1 x
p2 : Finset ι
hp2 : ↑p2 ⊆ T
f2 : ι → Set Ω
ht2_m : ∀ x ∈ p2, f2 x ∈ s x
ht2_eq : t2 = ⋂ x ∈ p2, f2 x
g : ι → Set Ω := fun i ↦ (if i ∈ p1 then f1 i else univ) ∩ if i ∈ p2 then f2 i else univ
i : ι
hi_mem_union : i ∈ p1 ∪ p2
⊢ g i ∈ s i

Tactic:
rw [Finset.mem_union] at hi_mem_union

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
s : ι → Set (Set Ω)
S T : Set ι
h_indep : iIndepSets s κ μ
hST : Disjoint S T
t1 t2 : Set Ω
p1 : Finset ι
hp1 : ↑p1 ⊆ S
f1 : ι → Set Ω
ht1_m : ∀ x ∈ p1, f1 x ∈ s x
ht1_eq : t1 = ⋂ x ∈ p1, f1 x
p2 : Finset ι
hp2 : ↑p2 ⊆ T
f2 : ι → Set Ω
ht2_m : ∀ x ∈ p2, f2 x ∈ s x
ht2_eq : t2 = ⋂ x ∈ p2, f2 x
g : ι → Set Ω := fun i ↦ (if i ∈ p1 then f1 i else univ) ∩ if i ∈ p2 then f2 i else univ
i : ι
hi_mem_union : i ∈ p1 ∨ i ∈ p2
⊢ g i ∈ s i
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: γ : Type u_1
Ω : Type u_2
mΩ : MeasurableSpace Ω
inst✝² : PseudoEMetricSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
F : Filter γ
inst✝ : F.IsCountablyGenerated
μs : γ → ProbabilityMeasure Ω
μ : ProbabilityMeasure Ω
hne : F.NeBot
h :
  ∀ (f : Ω → ℝ),
    (∃ C, ∀ (x y : Ω), dist (f x) (f y) ≤ C) →
      (∃ L, LipschitzWith L f) → Tendsto (fun i ↦ ∫ (ω : Ω), f ω ∂↑(μs i)) F (𝓝 (∫ (ω : Ω), f ω ∂↑μ))
s : Set Ω
hs : IsClosed[PseudoEMetricSpace.toUniformSpace.toTopologicalSpace] s
ε : ℝ
ε_pos : 0 < ε
n : ℕ
ω : Ω
⊢ 0 < 1 / (↑n + 1)

Tactic:
by positivity

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

Goal state before:
pp: γ : Type u_1
Ω : Type u_2
mΩ : MeasurableSpace Ω
inst✝² : PseudoEMetricSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
F : Filter γ
inst✝ : F.IsCountablyGenerated
μs : γ → ProbabilityMeasure Ω
μ : ProbabilityMeasure Ω
hne : F.NeBot
h :
  ∀ (f : Ω → ℝ),
    (∃ C, ∀ (x y : Ω), dist (f x) (f y) ≤ C) →
      (∃ L, LipschitzWith L f) → Tendsto (fun i ↦ ∫ (ω : Ω), f ω ∂↑(μs i)) F (𝓝 (∫ (ω : Ω), f ω ∂↑μ))
s : Set Ω
hs : IsClosed[PseudoEMetricSpace.toUniformSpace.toTopologicalSpace] s
ε : ℝ
ε_pos : 0 < ε
fs : ℕ → Ω → ℝ := fun n ω ↦ ↑((thickenedIndicator ⋯ s) ω)
x✝ : ℕ
⊢ 0 < 1 / (↑x✝ + 1)

Tactic:
by positivity

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

Goal state before:
pp: γ : Type u_1
Ω : Type u_2
mΩ : MeasurableSpace Ω
inst✝² : PseudoEMetricSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
F : Filter γ
inst✝ : F.IsCountablyGenerated
μs : γ → ProbabilityMeasure Ω
μ : ProbabilityMeasure Ω
hne : F.NeBot
h :
  ∀ (f : Ω → ℝ),
    (∃ C, ∀ (x y : Ω), dist (f x) (f y) ≤ C) →
      (∃ L, LipschitzWith L f) → Tendsto (fun i ↦ ∫ (ω : Ω), f ω ∂↑(μs i)) F (𝓝 (∫ (ω : Ω), f ω ∂↑μ))
s : Set Ω
hs : IsClosed[PseudoEMetricSpace.toUniformSpace.toTopologicalSpace] s
ε : ℝ
ε_pos : 0 < ε
fs : ℕ → Ω → ℝ := fun n ω ↦ ↑((thickenedIndicator ⋯ s) ω)
key₁ : Tendsto (fun n ↦ ∫ (ω : Ω), fs n ω ∂↑μ) atTop (𝓝 ((↑μ).real s))
room₁ : (↑μ).real s < (↑μ).real s + ε / 2
M : ℕ
hM : ∀ (b : ℕ), M ≤ b → ∫ (ω : Ω), fs b ω ∂↑μ < (↑μ).real s + ε / 2
⊢ 0 < 1 / (↑M + 1)

Tactic:
by positivity

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

Goal state before:
pp: case inr
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_Indep : iIndepFun f κ μ
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}
⊢ IndepFun (fun a i ↦ f (↑i) a) (fun a i ↦ f (↑i) a) η μ

Tactic:
let πS := { s : Set Ω | ∃ t ∈ πSβ, (fun a (i : S) => f i a) ⁻¹' t = s }

Goal state after:
case inr
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_Indep : iIndepFun f κ μ
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}
⊢ IndepFun (fun a i ↦ f (↑i) a) (fun a i ↦ f (↑i) a) η μ
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: γ : Type u_1
Ω : Type u_2
mΩ : MeasurableSpace Ω
inst✝² : PseudoEMetricSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
F : Filter γ
inst✝ : F.IsCountablyGenerated
μs : γ → ProbabilityMeasure Ω
μ : ProbabilityMeasure Ω
hne : F.NeBot
h :
  ∀ (f : Ω → ℝ),
    (∃ C, ∀ (x y : Ω), dist (f x) (f y) ≤ C) →
      (∃ L, LipschitzWith L f) → Tendsto (fun i ↦ ∫ (ω : Ω), f ω ∂↑(μs i)) F (𝓝 (∫ (ω : Ω), f ω ∂↑μ))
s : Set Ω
hs : IsClosed[PseudoEMetricSpace.toUniformSpace.toTopologicalSpace] s
ε : ℝ
ε_pos : 0 < ε
fs : ℕ → Ω → ℝ := fun n ω ↦ ↑((thickenedIndicator ⋯ s) ω)
key₁ : Tendsto (fun n ↦ ∫ (ω : Ω), fs n ω ∂↑μ) atTop (𝓝 ((↑μ).real s))
room₁ : (↑μ).real s < (↑μ).real s + ε / 2
M : ℕ
hM : ∀ (b : ℕ), M ≤ b → ∫ (ω : Ω), fs b ω ∂↑μ < (↑μ).real s + ε / 2
key₂ : Tendsto (fun i ↦ ∫ (ω : Ω), fs M ω ∂↑(μs i)) F (𝓝 (∫ (ω : Ω), fs M ω ∂↑μ))
room₂ : ∫ (a : Ω), fs M a ∂↑μ < ∫ (a : Ω), fs M a ∂↑μ + ε / 2
x : γ
hx : ∫ (ω : Ω), fs M ω ∂↑(μs x) ≤ ∫ (a : Ω), fs M a ∂↑μ + ε / 2
⊢ 0 < 1 / (↑M + 1)

Tactic:
by positivity

Goal state after:
Module: Mathlib.Probability.Density

Goal state before:
pp: Ω : Type u_1
G : Type u_2
mΩ : MeasurableSpace Ω
ℙ : Measure Ω
inst✝⁶ : Group G
mG : MeasurableSpace G
inst✝⁵ : MeasurableMul₂ G
inst✝⁴ : MeasurableInv G
μ : Measure G
inst✝³ : μ.IsMulLeftInvariant
X Y : Ω → G
inst✝² : SFinite μ
inst✝¹ : HasPDF X ℙ μ
inst✝ : HasPDF Y ℙ μ
σX : SigmaFinite (map X ℙ)
σY : SigmaFinite (map Y ℙ)
hXY : X ⟂ᵢ[ℙ] Y
⊢ HasPDF (X * Y) ℙ μ

Tactic:
have : AEMeasurable X ℙ := HasPDF.aemeasurable' μ
  have : AEMeasurable Y ℙ := HasPDF.aemeasurable' μ
  rw [hasPDF_iff_of_aemeasurable (by fun_prop),
    hXY.map_mul_eq_map_mconv_map₀' (by fun_prop) (by fun_prop) σX σY]
  refine ⟨?_, mconv_absolutelyContinuous HasPDF.absolutelyContinuous⟩
  apply HaveLebesgueDecomposition.mconv <;> exact HasPDF.absolutelyContinuous

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

Goal state before:
pp: case add
Ω : Type u_1
Mf mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
c : ℝ≥0∞
T : Set Ω
h_meas_T : MeasurableSet T
h_ind : IndepSets {s | MeasurableSet s} {T} μ
h_mul_indicator : ∀ (g : Ω → ℝ≥0∞), Measurable g → Measurable fun a ↦ g a * T.indicator (fun x ↦ c) a
⊢ ∀ ⦃f g : Ω → ℝ≥0∞⦄,
    Disjoint (Function.support f) (Function.support g) →
      Measurable f →
        Measurable g →
          ∫⁻ (ω : Ω), f ω * T.indicator (fun x ↦ c) ω ∂μ =
              (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ →
            ∫⁻ (ω : Ω), g ω * T.indicator (fun x ↦ c) ω ∂μ =
                (∫⁻ (ω : Ω), g ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ →
              ∫⁻ (ω : Ω), (f + g) ω * T.indicator (fun x ↦ c) ω ∂μ =
                (∫⁻ (ω : Ω), (f + g) ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ

Tactic:
intro f' g _ h_meas_f' _ h_ind_f' h_ind_g

Goal state after:
case add
Ω : Type u_1
Mf mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
c : ℝ≥0∞
T : Set Ω
h_meas_T : MeasurableSet T
h_ind : IndepSets {s | MeasurableSet s} {T} μ
h_mul_indicator : ∀ (g : Ω → ℝ≥0∞), Measurable g → Measurable fun a ↦ g a * T.indicator (fun x ↦ c) a
f' g : Ω → ℝ≥0∞
a✝¹ : Disjoint (Function.support f') (Function.support g)
h_meas_f' : Measurable f'
a✝ : Measurable g
h_ind_f' :
  ∫⁻ (ω : Ω), f' ω * T.indicator (fun x ↦ c) ω ∂μ = (∫⁻ (ω : Ω), f' ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ
h_ind_g :
  ∫⁻ (ω : Ω), g ω * T.indicator (fun x ↦ c) ω ∂μ = (∫⁻ (ω : Ω), g ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ
⊢ ∫⁻ (ω : Ω), (f' + g) ω * T.indicator (fun x ↦ c) ω ∂μ =
    (∫⁻ (ω : Ω), (f' + g) ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
hX : MemLp X 2 μ
h : ∫ (ω : Ω), (X ω - ∫ (x : Ω), X x ∂μ) ^ 2 ∂μ = 0
x✝ : Ω
⊢ 0 x✝ ≤ (X x✝ - ∫ (x : Ω), X x ∂μ) ^ 2

Tactic:
by positivity

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:
exact hu.comp_aemeasurable h.aemeasurable_snd

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
inst✝⁴ : MeasurableSpace α
E : Type u_5
inst✝³ : MeasurableSpace E
inst✝² : NormedAddCommGroup E
inst✝¹ : BorelSpace E
μ : Measure α
inst✝ : IsFiniteMeasure μ
ι : Type u_6
f : ι → α → E
j : ι
p : ℝ≥0∞
hp : 1 ≤ p
hp' : p ≠ ∞
hℒp : MemLp (f j) p μ
hfmeas : ∀ (i : ι), StronglyMeasurable (f i)
hf : ∀ (i : ι), IdentDistrib (f i) (f j) μ μ
ε : ℝ
hε : 0 < ε
hι : Nonempty ι
C : ℝ
hC₁ : 0 < C
hC₂ : eLpNorm ({x | C ≤ ↑‖f j x‖₊}.indicator (f j)) p μ ≤ ENNReal.ofReal ε
i : ι
this : {x | ⟨C, ⋯⟩ ≤ ‖f i x‖₊} = {x | C ≤ ‖f i x‖}
F : E → ℝ := fun x ↦ if ⟨C, ⋯⟩ ≤ ‖x‖₊ then ‖x‖ else 0
F_meas : Measurable F
k : ι
x : α
⊢ {x | C ≤ ‖f k x‖}.indicator (fun a ↦ ‖f k a‖) x = (F ∘ f k) x

Tactic:
simp only [Set.indicator, Set.mem_ofPred_eq]

Goal state after:
α : Type u_1
inst✝⁴ : MeasurableSpace α
E : Type u_5
inst✝³ : MeasurableSpace E
inst✝² : NormedAddCommGroup E
inst✝¹ : BorelSpace E
μ : Measure α
inst✝ : IsFiniteMeasure μ
ι : Type u_6
f : ι → α → E
j : ι
p : ℝ≥0∞
hp : 1 ≤ p
hp' : p ≠ ∞
hℒp : MemLp (f j) p μ
hfmeas : ∀ (i : ι), StronglyMeasurable (f i)
hf : ∀ (i : ι), IdentDistrib (f i) (f j) μ μ
ε : ℝ
hε : 0 < ε
hι : Nonempty ι
C : ℝ
hC₁ : 0 < C
hC₂ : eLpNorm ({x | C ≤ ↑‖f j x‖₊}.indicator (f j)) p μ ≤ ENNReal.ofReal ε
i : ι
this : {x | ⟨C, ⋯⟩ ≤ ‖f i x‖₊} = {x | C ≤ ‖f i x‖}
F : E → ℝ := fun x ↦ if ⟨C, ⋯⟩ ≤ ‖x‖₊ then ‖x‖ else 0
F_meas : Measurable F
k : ι
x : α
⊢ (if C ≤ ‖f k x‖ then ‖f k x‖ else 0) = (F ∘ f k) x
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
⊢ ε / ↑L > 0

Tactic:
by positivity

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

Goal state before:
pp: Ω : Type u_1
ι : Type u_2
m : MeasurableSpace Ω
inst✝ : LinearOrder ι
𝓕 : Filtration ι m
i : ι
this✝ : TopologicalSpace ι := Preorder.topology ι
this : OrderTopology ι
j : ι
hij : j > i
hIoo : Set.Ioo i j = ∅
hcov : i ⋖ j
⊢ ↑𝓕₊ i = ↑𝓕 i

Tactic:
exact rightCont_eq_of_nhdsGT_eq_bot _ <| CovBy.nhdsGT hcov

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'
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'|
hXY : ∀ (ε : ℝ), 0 < ε → Tendsto (fun i ↦ μ''.real {x | ε ≤ ‖(Y - X) i x‖}) l (𝓝 0)
⊢ 0 < ε / 2

Tactic:
by positivity

Goal state after: