mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.MeasureTheory.VectorMeasure.Decomposition.Lebesgue

Goal state before:
pp: case a
α : Type u_1
m : MeasurableSpace α
μ : Measure α
c : ComplexMeasure α
inst✝ : c.HaveLebesgueDecomposition μ
i : Set α
hi : MeasurableSet i
⊢ ((im c).singularPart μ + μ.withDensityᵥ ((im c).rnDeriv μ)) i = { re := (re c) i, im := (im c) i }.im

Tactic:
c.im.singularPart_add_withDensity_rnDeriv_eq μ

Goal state after:
case a
α : Type u_1
m : MeasurableSpace α
μ : Measure α
c : ComplexMeasure α
inst✝ : c.HaveLebesgueDecomposition μ
i : Set α
hi : MeasurableSet i
⊢ (im c) i = { re := (re c) i, im := (im c) i }.im
Module: Mathlib.MeasureTheory.Measure.HasOuterApproxClosed

Goal state before:
pp: Ω : Type u_1
inst✝⁴ : MeasurableSpace Ω
inst✝³ : TopologicalSpace Ω
inst✝² : HasOuterApproxClosed Ω
inst✝¹ : OpensMeasurableSpace Ω
μ ν : Measure Ω
inst✝ : IsFiniteMeasure μ
h : ∀ (f : Ω →ᵇ ℝ≥0), ∫⁻ (x : Ω), ↑(f x) ∂μ = ∫⁻ (x : Ω), ↑(f x) ∂ν
F : Set Ω
F_closed : IsClosed[inst✝³] F
ν_finite : IsFiniteMeasure ν
obs_μ : Tendsto (fun n ↦ ∫⁻ (x : Ω), ↑((F_closed.apprSeq n) x) ∂μ) atTop (𝓝 (μ F))
obs_ν : Tendsto (fun n ↦ ∫⁻ (x : Ω), ↑((F_closed.apprSeq n) x) ∂ν) atTop (𝓝 (ν F))
⊢ μ F = ν F

Tactic:
h

Goal state after:
Ω : Type u_1
inst✝⁴ : MeasurableSpace Ω
inst✝³ : TopologicalSpace Ω
inst✝² : HasOuterApproxClosed Ω
inst✝¹ : OpensMeasurableSpace Ω
μ ν : Measure Ω
inst✝ : IsFiniteMeasure μ
h : ∀ (f : Ω →ᵇ ℝ≥0), ∫⁻ (x : Ω), ↑(f x) ∂μ = ∫⁻ (x : Ω), ↑(f x) ∂ν
F : Set Ω
F_closed : IsClosed[inst✝³] F
ν_finite : IsFiniteMeasure ν
obs_ν : Tendsto (fun n ↦ ∫⁻ (x : Ω), ↑((F_closed.apprSeq n) x) ∂ν) atTop (𝓝 (ν F))
obs_μ : Tendsto (fun n ↦ ∫⁻ (x : Ω), ↑((F_closed.apprSeq n) x) ∂ν) atTop (𝓝 (μ F))
⊢ μ F = ν F
Module: Mathlib.MeasureTheory.Function.UniformIntegrable

Goal state before:
pp: 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), AEStronglyMeasurable (f i) μ
h : ∀ (ε : ℝ), 0 < ε → ∃ C, ∀ (i : ι), eLpNorm ({x | C ≤ ‖f i x‖₊}.indicator (f i)) p μ ≤ ENNReal.ofReal ε
⊢ UnifIntegrable f p μ

Tactic:
set g : ι → α → β := fun i => (hf i).choose
  refine
    (unifIntegrable_of' hp hp' (fun i => (Exists.choose_spec <| hf i).1) fun ε hε => ?_).ae_eq
      fun i => (Exists.choose_spec <| hf i).2.symm
  obtain ⟨C, hC⟩ := h ε hε
  have hCg : ∀ i, eLpNorm ({ x | C ≤ ‖g i x‖₊ }.indicator (g i)) p μ ≤ ENNReal.ofReal ε := by
    intro i
    refine le_trans (le_of_eq <| eLpNorm_congr_ae ?_) (hC i)
    filter_upwards [(Exists.choose_spec <| hf i).2] with x hx
    by_cases hfx : x ∈ { x | C ≤ ‖f i x‖₊ }
    · rw [Set.indicator_of_mem hfx, Set.indicator_of_mem, hx]
      rwa [Set.mem_ofPred, hx] at hfx
    · rw [Set.indicator_of_notMem hfx, Set.indicator_of_notMem]
      rwa [Set.mem_ofPred, hx] at hfx
  refine ⟨max C 1, lt_max_of_lt_right one_pos, fun i => le_trans (eLpNorm_mono fun x => ?_) (hCg i)⟩
  rw [norm_indicator_eq_indicator_norm, norm_indicator_eq_indicator_norm]
  grw [← le_max_left]

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

Goal state before:
pp: case pos
Ω : Type u_1
inst✝² : Nonempty Ω
m0 : MeasurableSpace Ω
μ : FiniteMeasure Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
γ : Type u_2
F : Filter γ
μs : γ → FiniteMeasure Ω
μs_lim : Tendsto (fun i ↦ (μs i).normalize) F (𝓝 μ.normalize)
mass_lim : Tendsto (fun i ↦ (μs i).mass) F (𝓝 μ.mass)
f : Ω →ᵇ ℝ≥0
h_mass : μ.mass = 0
⊢ Tendsto (fun i ↦ (μs i).testAgainstNN f) F (𝓝 (μ.testAgainstNN f))

pp: case neg
Ω : Type u_1
inst✝² : Nonempty Ω
m0 : MeasurableSpace Ω
μ : FiniteMeasure Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
γ : Type u_2
F : Filter γ
μs : γ → FiniteMeasure Ω
μs_lim : Tendsto (fun i ↦ (μs i).normalize) F (𝓝 μ.normalize)
mass_lim : Tendsto (fun i ↦ (μs i).mass) F (𝓝 μ.mass)
f : Ω →ᵇ ℝ≥0
h_mass : ¬μ.mass = 0
⊢ Tendsto (fun i ↦ (μs i).testAgainstNN f) F (𝓝 (μ.testAgainstNN f))

Tactic:
· simp only [μ.mass_zero_iff.mp h_mass, zero_testAgainstNN_apply, zero_mass] at mass_lim ⊢
    exact tendsto_zero_testAgainstNN_of_tendsto_zero_mass mass_lim f

Goal state after:
case neg
Ω : Type u_1
inst✝² : Nonempty Ω
m0 : MeasurableSpace Ω
μ : FiniteMeasure Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
γ : Type u_2
F : Filter γ
μs : γ → FiniteMeasure Ω
μs_lim : Tendsto (fun i ↦ (μs i).normalize) F (𝓝 μ.normalize)
mass_lim : Tendsto (fun i ↦ (μs i).mass) F (𝓝 μ.mass)
f : Ω →ᵇ ℝ≥0
h_mass : ¬μ.mass = 0
⊢ Tendsto (fun i ↦ (μs i).testAgainstNN f) F (𝓝 (μ.testAgainstNN f))
Module: Mathlib.MeasureTheory.Measure.FiniteMeasure

Goal state before:
pp: Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
γ : Type u_2
F : Filter γ
μs : γ → FiniteMeasure Ω
μ : FiniteMeasure Ω
h : ∀ (f : Ω →ᵇ ℝ), Tendsto (fun i ↦ ∫ (x : Ω), f x ∂↑(μs i)) F (𝓝 (∫ (x : Ω), f x ∂↑μ))
f : Ω →ᵇ ℝ≥0
lip : LipschitzWith 1 NNReal.toReal
f₀ : Ω →ᵇ ℝ := comp NNReal.toReal lip f
_def_f₀ : f₀ = comp NNReal.toReal lip f
f₀_eq : ⇑f₀ = NNReal.toReal ∘ ⇑f
f₀_nn : 0 ≤ ⇑f₀
f₀_ae_nn : 0 ≤ᵐ[↑μ] ⇑f₀
f₀_ae_nns : ∀ (i : γ), 0 ≤ᵐ[↑(μs i)] ⇑f₀
aux : ∫ (a : Ω), f₀ a ∂↑μ = (∫⁻ (a : Ω), ENNReal.ofReal (f₀ a) ∂↑μ).toReal
⊢ Tendsto (fun n ↦ (∫⁻ (x : Ω), ↑(f x) ∂↑(μs n)).toReal) F (𝓝 (∫⁻ (x : Ω), ↑(f x) ∂↑μ).toReal)

Tactic:
have auxs := fun i ↦
    integral_eq_lintegral_of_nonneg_ae (f₀_ae_nns i) f₀.continuous.measurable.aestronglyMeasurable

Goal state after:
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
γ : Type u_2
F : Filter γ
μs : γ → FiniteMeasure Ω
μ : FiniteMeasure Ω
h : ∀ (f : Ω →ᵇ ℝ), Tendsto (fun i ↦ ∫ (x : Ω), f x ∂↑(μs i)) F (𝓝 (∫ (x : Ω), f x ∂↑μ))
f : Ω →ᵇ ℝ≥0
lip : LipschitzWith 1 NNReal.toReal
f₀ : Ω →ᵇ ℝ := comp NNReal.toReal lip f
_def_f₀ : f₀ = comp NNReal.toReal lip f
f₀_eq : ⇑f₀ = NNReal.toReal ∘ ⇑f
f₀_nn : 0 ≤ ⇑f₀
f₀_ae_nn : 0 ≤ᵐ[↑μ] ⇑f₀
f₀_ae_nns : ∀ (i : γ), 0 ≤ᵐ[↑(μs i)] ⇑f₀
aux : ∫ (a : Ω), f₀ a ∂↑μ = (∫⁻ (a : Ω), ENNReal.ofReal (f₀ a) ∂↑μ).toReal
auxs : ∀ (i : γ), ∫ (a : Ω), f₀ a ∂↑(μs i) = (∫⁻ (a : Ω), ENNReal.ofReal (f₀ a) ∂↑(μs i)).toReal
⊢ Tendsto (fun n ↦ (∫⁻ (x : Ω), ↑(f x) ∂↑(μs n)).toReal) F (𝓝 (∫⁻ (x : Ω), ↑(f x) ∂↑μ).toReal)
Module: Mathlib.MeasureTheory.Measure.FiniteMeasure

Goal state before:
pp: Ω' : Type u_2
inst✝⁶ : MeasurableSpace Ω'
inst✝⁵ : TopologicalSpace Ω'
inst✝⁴ : BorelSpace Ω'
Ω : Type u_3
inst✝³ : MeasurableSpace Ω
inst✝² : TopologicalSpace Ω
inst✝¹ : BorelSpace Ω
inst✝ : NormalSpace Ω'
f : Ω → Ω'
hf : IsClosedEmbedding f
M : Set (FiniteMeasure Ω') := {μ | μ (range f)ᶜ = 0}
⊢ IsEmbedding fun μ ↦ μ.map f

Tactic:
have A : IsEmbedding (Subtype.val : M → FiniteMeasure Ω') := IsEmbedding.subtypeVal

Goal state after:
Ω' : Type u_2
inst✝⁶ : MeasurableSpace Ω'
inst✝⁵ : TopologicalSpace Ω'
inst✝⁴ : BorelSpace Ω'
Ω : Type u_3
inst✝³ : MeasurableSpace Ω
inst✝² : TopologicalSpace Ω
inst✝¹ : BorelSpace Ω
inst✝ : NormalSpace Ω'
f : Ω → Ω'
hf : IsClosedEmbedding f
M : Set (FiniteMeasure Ω') := {μ | μ (range f)ᶜ = 0}
A : IsEmbedding Subtype.val
⊢ IsEmbedding fun μ ↦ μ.map f
Module: Mathlib.MeasureTheory.Function.UniformIntegrable

Goal state before:
pp: case refine_2
α : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace α
μ : Measure α
inst✝² : NormedAddCommGroup β
p : ℝ≥0∞
κ : Type u_4
u : Filter κ
inst✝¹ : u.NeBot
inst✝ : u.IsCountablyGenerated
fn : ι → α → β
hUI : UniformIntegrable fn p μ
⊢ ∃ C, ∀ (i : ↑{g | ∃ ni, ∀ᵐ (x : α) ∂μ, Tendsto (fun n ↦ fn (ni n) x) u (𝓝 (g x))}), eLpNorm ((fun f ↦ ↑f) i) p μ ≤ ↑C

Tactic:
· obtain ⟨C, hC⟩ := hUI.2.2
    exact ⟨C, fun ⟨f, s, hs⟩ => Lp.eLpNorm_le_of_ae_tendsto
      (Eventually.of_forall fun n => hC (s n)) (fun n => hUI.1 (s n)) hs⟩

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

Goal state before:
pp: case e'_3.e'_6
Ω : Type u_10
Ω' : Type u_11
mΩ : MeasurableSpace Ω
mΩ' : MeasurableSpace Ω'
μ : Measure Ω
ν : Measure Ω'
inst✝³ : IsProbabilityMeasure μ
inst✝² : IsProbabilityMeasure ν
𝓧 : Type u_12
𝓨 : Type u_13
inst✝¹ : MeasurableSpace 𝓧
inst✝ : MeasurableSpace 𝓨
X : Ω → 𝓧
Y : Ω' → 𝓨
mX : Measurable X
mY : Measurable Y
⊢ Measure.map (fun ω ↦ Y ω.2) (μ.prod ν) = Measure.map Y ν

Tactic:
· rw [← Function.comp_def, ← Measure.map_map mY measurable_snd, Measure.map_snd_prod,
      measure_univ, one_smul]

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

Goal state before:
pp: case pos
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
h :
  ∀ (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)
u : Set α
s : Set β
t : Set γ
hu : MeasurableSet u
hs : MeasurableSet s
ht : MeasurableSet t
h_set_eq : ∀ (ω : α), Prod.mk ω ⁻¹' u ×ˢ s ×ˢ t = if ω ∈ u then s ×ˢ t else ∅
ω : α
hω : (κ ω) (f ⁻¹' s ∩ g ⁻¹' t) = (κ ω) (f ⁻¹' s) * (κ ω) (g ⁻¹' t)
hωu : ω ∈ u
⊢ (κ ω) (f ⁻¹' s) * (κ ω) (g ⁻¹' t) = ((κ.map f) ω) s * ((κ.map g) ω) t

Tactic:
map_apply' _ (by fun_prop),

Goal state after:
case pos
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
h :
  ∀ (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)
u : Set α
s : Set β
t : Set γ
hu : MeasurableSet u
hs : MeasurableSet s
ht : MeasurableSet t
h_set_eq : ∀ (ω : α), Prod.mk ω ⁻¹' u ×ˢ s ×ˢ t = if ω ∈ u then s ×ˢ t else ∅
ω : α
hω : (κ ω) (f ⁻¹' s ∩ g ⁻¹' t) = (κ ω) (f ⁻¹' s) * (κ ω) (g ⁻¹' t)
hωu : ω ∈ u
⊢ (κ ω) (f ⁻¹' s) * (κ ω) (g ⁻¹' t) = (κ ω) (f ⁻¹' s) * ((κ.map g) ω) t

case pos.hs
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
h :
  ∀ (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)
u : Set α
s : Set β
t : Set γ
hu : MeasurableSet u
hs : MeasurableSet s
ht : MeasurableSet t
h_set_eq : ∀ (ω : α), Prod.mk ω ⁻¹' u ×ˢ s ×ˢ t = if ω ∈ u then s ×ˢ t else ∅
ω : α
hω : (κ ω) (f ⁻¹' s ∩ g ⁻¹' t) = (κ ω) (f ⁻¹' s) * (κ ω) (g ⁻¹' t)
hωu : ω ∈ u
⊢ MeasurableSet s
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: case mp
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
⊢ Tendsto μs F (𝓝 μ) →
    ∀ (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))

Tactic:
intro h f hf_bounded hf_lip
    simp_rw [ProbabilityMeasure.tendsto_iff_forall_integral_tendsto] at h
    let f' : BoundedContinuousFunction Ω ℝ :=
    { toFun := f
      continuous_toFun := hf_lip.choose_spec.continuous
      map_bounded' := hf_bounded }
    simpa using! h f'

Goal state after:
Module: Mathlib.Probability.Density

Goal state before:
pp: case refine_1
Ω : Type u_1
E : Type u_2
inst✝ : MeasurableSpace E
x✝ : MeasurableSpace Ω
X : Ω → E
ℙ : Measure Ω
μ : Measure E
hX : AEMeasurable X ℙ
f : E → ℝ≥0∞
hf : AEMeasurable f μ
h : map X ℙ = μ.withDensity f
⊢ (map X ℙ).HaveLebesgueDecomposition μ

Tactic:
h

Goal state after:
case refine_1
Ω : Type u_1
E : Type u_2
inst✝ : MeasurableSpace E
x✝ : MeasurableSpace Ω
X : Ω → E
ℙ : Measure Ω
μ : Measure E
hX : AEMeasurable X ℙ
f : E → ℝ≥0∞
hf : AEMeasurable f μ
h : map X ℙ = μ.withDensity f
⊢ (μ.withDensity f).HaveLebesgueDecomposition μ
Module: Mathlib.Probability.Density

Goal state before:
pp: case refine_2
Ω : Type u_1
E : Type u_2
inst✝ : MeasurableSpace E
x✝ : MeasurableSpace Ω
X : Ω → E
ℙ : Measure Ω
μ : Measure E
hX : AEMeasurable X ℙ
f : E → ℝ≥0∞
hf : AEMeasurable f μ
h : map X ℙ = μ.withDensity f
⊢ map X ℙ ≪ μ

Tactic:
h

Goal state after:
case refine_2
Ω : Type u_1
E : Type u_2
inst✝ : MeasurableSpace E
x✝ : MeasurableSpace Ω
X : Ω → E
ℙ : Measure Ω
μ : Measure E
hX : AEMeasurable X ℙ
f : E → ℝ≥0∞
hf : AEMeasurable f μ
h : map X ℙ = μ.withDensity f
⊢ μ.withDensity f ≪ μ
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
⊢ ∫⁻ (ω : Ω), ‖X ω - ∫ (x : Ω), X x ∂μ‖ₑ ^ 2 ∂μ = ∫⁻ (ω : Ω), ‖Y ω - ∫ (x : Ω), Y x ∂μ‖ₑ ^ 2 ∂μ

Tactic:
integral_congr_ae h

Goal state after:
Ω : Type u_1
mΩ : MeasurableSpace Ω
X Y : Ω → ℝ
μ : Measure Ω
h : X =ᵐ[μ] Y
⊢ ∫⁻ (ω : Ω), ‖X ω - ∫ (a : Ω), Y a ∂μ‖ₑ ^ 2 ∂μ = ∫⁻ (ω : Ω), ‖Y ω - ∫ (a : Ω), Y a ∂μ‖ₑ ^ 2 ∂μ
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: case e_f
Ω : Type u_1
mΩ : MeasurableSpace Ω
c : ℝ
X : Ω → ℝ
μ : Measure Ω
ω : Ω
⊢ (‖c‖ₑ * ‖X ω - ∫ (a : Ω), X a ∂μ‖ₑ) ^ 2 = ENNReal.ofReal (c ^ 2) * ‖X ω - ∫ (x : Ω), X x ∂μ‖ₑ ^ 2

Tactic:
mul_pow,

Goal state after:
case e_f
Ω : Type u_1
mΩ : MeasurableSpace Ω
c : ℝ
X : Ω → ℝ
μ : Measure Ω
ω : Ω
⊢ ‖c‖ₑ ^ 2 * ‖X ω - ∫ (a : Ω), X a ∂μ‖ₑ ^ 2 = ENNReal.ofReal (c ^ 2) * ‖X ω - ∫ (x : Ω), X x ∂μ‖ₑ ^ 2
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: case pos
Ω : Type u_1
mΩ : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
inst✝ : IsProbabilityMeasure μ
hX : AEStronglyMeasurable X μ
c : ℝ
hX_Lp : MemLp X 2 μ
hX_int : Integrable X μ
⊢ Var[fun ω ↦ X ω + c; μ] = Var[X; μ]

Tactic:
rw [variance_eq_integral (hX.add_const _).aemeasurable,
      integral_add hX_int (by fun_prop), integral_const, variance_eq_integral hX.aemeasurable]

Goal state after:
case pos
Ω : Type u_1
mΩ : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
inst✝ : IsProbabilityMeasure μ
hX : AEStronglyMeasurable X μ
c : ℝ
hX_Lp : MemLp X 2 μ
hX_int : Integrable X μ
⊢ ∫ (ω : Ω), (X ω + c - (∫ (a : Ω), X a ∂μ + μ.real Set.univ • c)) ^ 2 ∂μ = ∫ (ω : Ω), (X ω - ∫ (x : Ω), X x ∂μ) ^ 2 ∂μ
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
⊢ cov[c • X, Y; μ] = c * cov[X, Y; μ]

Tactic:
simp_rw [covariance, Pi.smul_apply, smul_eq_mul, ← integral_const_mul, ← mul_assoc, mul_sub,
    integral_const_mul]

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
E : Type u_5
F : Type u_6
G : Type u_7
inst✝⁸ : TopologicalSpace E
inst✝⁷ : ContinuousENorm E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : OpensMeasurableSpace E
inst✝⁴ : NormedAddGroup F
inst✝³ : MeasurableSpace F
inst✝² : OpensMeasurableSpace F
inst✝¹ : TopologicalSpace G
inst✝ : ContinuousENorm G
X : Ω → E
Y : Ω → F
hXY : X ⟂ᵢ[μ] Y
B : E → F → G
c : ℝ≥0
hc : c ≠ 0
hB : ∀ (x : E) (y : F), ↑c * ‖x‖ₑ * ‖y‖ₑ ≤ ‖B x y‖ₑ
h'XY : Integrable (fun ω ↦ B (X ω) (Y ω)) μ
hX : AEStronglyMeasurable X μ
hY : AEStronglyMeasurable Y μ
h'Y : ¬Y =ᵐ[μ] 0
I : ∫⁻ (ω : Ω), ‖Y ω‖ₑ ∂μ ≠ 0
H : ∫⁻ (a : Ω), ‖X a‖ₑ ∂μ = ∞
J : (fun x ↦ ‖X x‖ₑ) ⟂ᵢ[μ] fun x ↦ ‖Y x‖ₑ
⊢ ∞ = ↑c * ((∫⁻ (ω : Ω), ‖X ω‖ₑ ∂μ) * ∫⁻ (ω : Ω), ‖Y ω‖ₑ ∂μ)

Tactic:
by
      rw [H, top_mul I, mul_top (by simpa)]

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

Goal state before:
pp: case pos
Ω : Type u_1
𝕜 : Type u_2
inst✝¹⁴ : RCLike 𝕜
mΩ : MeasurableSpace Ω
μ : Measure Ω
𝓧 : Type u_3
𝓨 : Type u_4
E : Type u_5
F : Type u_6
G : Type u_7
inst✝¹³ : MeasurableSpace 𝓧
inst✝¹² : MeasurableSpace 𝓨
inst✝¹¹ : NormedAddCommGroup E
inst✝¹⁰ : NormedSpace ℝ E
inst✝⁹ : NormedSpace 𝕜 E
inst✝⁸ : CompleteSpace E
inst✝⁷ : NormedAddCommGroup F
inst✝⁶ : NormedSpace ℝ F
inst✝⁵ : NormedSpace 𝕜 F
inst✝⁴ : CompleteSpace F
inst✝³ : NormedAddCommGroup G
inst✝² : NormedSpace ℝ G
inst✝¹ : NormedSpace 𝕜 G
inst✝ : CompleteSpace G
X : Ω → 𝓧
Y : Ω → 𝓨
f : 𝓧 → E
g : 𝓨 → F
hXY : X ⟂ᵢ[μ] Y
hX : AEMeasurable X μ
hY : AEMeasurable Y μ
hf : Integrable f (Measure.map X μ)
hg : Integrable g (Measure.map Y μ)
B : E →L[𝕜] F →L[𝕜] G
h : ∀ᵐ (ω : Ω) ∂μ, f (X ω) = 0
⊢ ∫ (ω : Ω), (B (f (X ω))) (g (Y ω)) ∂μ = (B (∫ (ω : Ω), f (X ω) ∂μ)) (∫ (ω : Ω), g (Y ω) ∂μ)

Tactic:
have h1 : ∀ᵐ ω ∂μ, B (f (X ω)) (g (Y ω)) = 0 := by
      filter_upwards [h] with ω hω
      simp [hω]
    simp [integral_congr_ae h1, integral_congr_ae h]

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsProbabilityMeasure μ
a b : ℝ
X : Ω → ℝ
h : ∀ᵐ (ω : Ω) ∂μ, X ω ∈ Set.Icc a b
hX : AEMeasurable X μ
ha : ∀ᵐ (ω : Ω) ∂μ, a ≤ X ω
hb : ∀ᵐ (ω : Ω) ∂μ, X ω ≤ b
hX_int₂ : Integrable (fun ω ↦ -X ω ^ 2) μ
hX_int₁ : Integrable (fun ω ↦ (a + b) * X ω) μ
⊢ Var[X; μ] ≤ (b - ∫ (x : Ω), X x ∂μ) * (∫ (x : Ω), X x ∂μ - a)

Tactic:
have h0 : 0 ≤ -μ[X ^ 2] + (a + b) * μ[X] - a * b :=
    calc
      _ ≤ ∫ ω, (b - X ω) * (X ω - a) ∂μ := by
        apply integral_nonneg_of_ae
        filter_upwards [ha, hb] with ω ha' hb'
        exact mul_nonneg (by linarith : 0 ≤ b - X ω) (by linarith : 0 ≤ X ω - a)
      _ = ∫ ω, -X ω ^ 2 + (a + b) * X ω - a * b ∂μ :=
        integral_congr_ae <| ae_of_all μ fun ω ↦ by ring
      _ = ∫ ω, - X ω ^ 2 + (a + b) * X ω ∂μ - ∫ _, a * b ∂μ :=
        integral_sub (by fun_prop) (integrable_const (a * b))
      _ = ∫ ω, - X ω ^ 2 + (a + b) * X ω ∂μ - a * b := by simp
      _ = - μ[X ^ 2] + (a + b) * μ[X] - a * b := by
        simp [← integral_neg, ← integral_const_mul, integral_add hX_int₂ hX_int₁]

Goal state after:
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsProbabilityMeasure μ
a b : ℝ
X : Ω → ℝ
h : ∀ᵐ (ω : Ω) ∂μ, X ω ∈ Set.Icc a b
hX : AEMeasurable X μ
ha : ∀ᵐ (ω : Ω) ∂μ, a ≤ X ω
hb : ∀ᵐ (ω : Ω) ∂μ, X ω ≤ b
hX_int₂ : Integrable (fun ω ↦ -X ω ^ 2) μ
hX_int₁ : Integrable (fun ω ↦ (a + b) * X ω) μ
h0 : 0 ≤ -∫ (x : Ω), (X ^ 2) x ∂μ + (a + b) * ∫ (x : Ω), X x ∂μ - a * b
⊢ Var[X; μ] ≤ (b - ∫ (x : Ω), X x ∂μ) * (∫ (x : Ω), X x ∂μ - a)
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
m : (i : ι) → MeasurableSpace (β i)
f : (i : ι) → Ω → β i
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), Measurable (f i)
i j k : ι
hik : i ≠ k
hjk : j ≠ k
h_right : f k = (fun p ↦ p ⟨k, ⋯⟩) ∘ fun a j ↦ f (↑j) a
h_meas_right : Measurable fun p ↦ p ⟨k, ⋯⟩
s : Finset ι := {i, j}
h_left : (fun ω ↦ (f i ω, f j ω)) = (fun p ↦ (p ⟨i, ⋯⟩, p ⟨j, ⋯⟩)) ∘ fun a j ↦ f (↑j) a
h_meas_left : Measurable fun p ↦ (p ⟨i, ⋯⟩, p ⟨j, ⋯⟩)
⊢ k ∉ s

Tactic:
simp only [s, Finset.mem_insert, Finset.mem_singleton, not_or]

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
m : (i : ι) → MeasurableSpace (β i)
f : (i : ι) → Ω → β i
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), Measurable (f i)
i j k : ι
hik : i ≠ k
hjk : j ≠ k
h_right : f k = (fun p ↦ p ⟨k, ⋯⟩) ∘ fun a j ↦ f (↑j) a
h_meas_right : Measurable fun p ↦ p ⟨k, ⋯⟩
s : Finset ι := {i, j}
h_left : (fun ω ↦ (f i ω, f j ω)) = (fun p ↦ (p ⟨i, ⋯⟩, p ⟨j, ⋯⟩)) ∘ fun a j ↦ f (↑j) a
h_meas_left : Measurable fun p ↦ (p ⟨i, ⋯⟩, p ⟨j, ⋯⟩)
⊢ ¬k = i ∧ ¬k = j
Module: Mathlib.MeasureTheory.Function.FactorsThrough

Goal state before:
pp: X : Type u_1
Y : Type u_2
Z : Type u_3
mY : MeasurableSpace Y
f : X → Y
g : X → Z
inst✝² : TopologicalSpace Z
inst✝¹ : PseudoMetrizableSpace Z
inst✝ : T1Space Z
hg : StronglyMeasurable g
⊢ Function.FactorsThrough g f

Tactic:
by
  borelize Z
  exact hg.measurable.factorsThrough

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

Goal state before:
pp: Ω : Type u_1
ι : Type u_2
m : MeasurableSpace Ω
inst✝ : PartialOrder ι
𝓕 : Filtration ι m
i : ι
hi : IsMax i
⊢ ↑𝓕₊ i = ↑𝓕 i

Tactic:
by
  let := Preorder.topology ι; have : OrderTopology ι := ⟨rfl⟩
  exact rightCont_eq_of_nhdsGT_eq_bot _ (hi.Ioi_eq ▸ nhdsWithin_empty i)

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, Y i ⁻¹' t i) ∩ ⋂ i ∈ s, f i = (⋂ i, Y i ⁻¹' t i) ∩ ⋂ i, if i ∈ s then f i else univ

Tactic:
congr 1
          simp only [Set.iInter_ite, Set.iInter_univ, Set.inter_univ]

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

Goal state before:
pp: case refine_2.inl
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)
i : ι
t✝ : Set Ω
n : ι
ht : MeasurableSet t✝
t : Set Ω
hn : n ≤ i
u : Set (β n)
left✝ : MeasurableSet u
hu' : ((s n).indicator fun x ↦ 1) ⁻¹' u = t
heq : ((s n).indicator fun x ↦ 1) ⁻¹' u = Set.univ
⊢ MeasurableSet t

Tactic:
heq

Goal state after:
case refine_2.inl
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)
i : ι
t✝ : Set Ω
n : ι
ht : MeasurableSet t✝
t : Set Ω
hn : n ≤ i
u : Set (β n)
left✝ : MeasurableSet u
hu' : Set.univ = t
heq : ((s n).indicator fun x ↦ 1) ⁻¹' u = Set.univ
⊢ MeasurableSet t
Module: Mathlib.Probability.Process.Filtration

Goal state before:
pp: case refine_2.inr.inl
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)
i : ι
t✝ : Set Ω
n : ι
ht : MeasurableSet t✝
t : Set Ω
hn : n ≤ i
u : Set (β n)
left✝ : MeasurableSet u
hu' : ((s n).indicator fun x ↦ 1) ⁻¹' u = t
heq : ((s n).indicator fun x ↦ 1) ⁻¹' u = s n
⊢ MeasurableSet t

Tactic:
heq

Goal state after:
case refine_2.inr.inl
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)
i : ι
t✝ : Set Ω
n : ι
ht : MeasurableSet t✝
t : Set Ω
hn : n ≤ i
u : Set (β n)
left✝ : MeasurableSet u
hu' : s n = t
heq : ((s n).indicator fun x ↦ 1) ⁻¹' u = s n
⊢ MeasurableSet t