mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Process.HittingTime

Goal state before:
pp: Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
n : ι
ω : Ω
m i : ι
hi : i ≤ m
⊢ hittingBtwn u s n m ω < i ↔ ∃ j ∈ Set.Ico n i, u j ω ∈ s

Tactic:
constructor <;> intro h'

Goal state after:
case mp
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
n : ι
ω : Ω
m i : ι
hi : i ≤ m
h' : hittingBtwn u s n m ω < i
⊢ ∃ j ∈ Set.Ico n i, u j ω ∈ s

case mpr
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
n : ι
ω : Ω
m i : ι
hi : i ≤ m
h' : ∃ j ∈ Set.Ico n i, u j ω ∈ s
⊢ hittingBtwn u s n m ω < i
Module: Mathlib.Probability.Process.HittingTime

Goal state before:
pp: Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
n i : ι
ω : Ω
⊢ hittingAfter u s n ω < ↑i ↔ ∃ j ∈ Set.Ico n i, u j ω ∈ s

Tactic:
constructor <;> intro h'

Goal state after:
case mp
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
n i : ι
ω : Ω
h' : hittingAfter u s n ω < ↑i
⊢ ∃ j ∈ Set.Ico n i, u j ω ∈ s

case mpr
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
n i : ι
ω : Ω
h' : ∃ j ∈ Set.Ico n i, u j ω ∈ s
⊢ hittingAfter u s n ω < ↑i
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: case pos
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N : ℕ
ω : Ω
hf : a ≤ f N ω
hab : a < b
hN : ¬N = 0
h₁ :
  ∀ (k : ℕ),
    ∑ n ∈ Finset.range N,
        (Set.Ico (lowerCrossingTime a b f N k ω) (upperCrossingTime a b f N (k + 1) ω)).indicator
          (fun m ↦ f (m + 1) ω - f m ω) n =
      stoppedValue f (fun ω ↦ ↑(upperCrossingTime a b f N (k + 1) ω)) ω -
        stoppedValue f (fun ω ↦ ↑(lowerCrossingTime a b f N k ω)) ω
x✝ : upcrossingsBefore a b f N ω ∈ Finset.range N
hi : upcrossingsBefore a b f N ω ∉ Finset.range (upcrossingsBefore a b f N ω)
⊢ 0 ≤
    stoppedValue f (fun ω_1 ↦ ↑(upperCrossingTime a b f N (upcrossingsBefore a b f N ω + 1) ω_1)) ω -
      stoppedValue f (fun ω_1 ↦ ↑(lowerCrossingTime a b f N (upcrossingsBefore a b f N ω) ω_1)) ω

Tactic:
simp only [stoppedValue]

Goal state after:
case pos
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N : ℕ
ω : Ω
hf : a ≤ f N ω
hab : a < b
hN : ¬N = 0
h₁ :
  ∀ (k : ℕ),
    ∑ n ∈ Finset.range N,
        (Set.Ico (lowerCrossingTime a b f N k ω) (upperCrossingTime a b f N (k + 1) ω)).indicator
          (fun m ↦ f (m + 1) ω - f m ω) n =
      stoppedValue f (fun ω ↦ ↑(upperCrossingTime a b f N (k + 1) ω)) ω -
        stoppedValue f (fun ω ↦ ↑(lowerCrossingTime a b f N k ω)) ω
x✝ : upcrossingsBefore a b f N ω ∈ Finset.range N
hi : upcrossingsBefore a b f N ω ∉ Finset.range (upcrossingsBefore a b f N ω)
⊢ 0 ≤
    f (↑(upperCrossingTime a b f N (upcrossingsBefore a b f N ω + 1) ω)).untopA ω -
      f (↑(lowerCrossingTime a b f N (upcrossingsBefore a b f N ω) ω)).untopA ω
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝³ : AddGroup ι
inst✝² : Preorder ι
inst✝¹ : AddRightMono ι
inst✝ : AddLeftMono ι
f : Filtration ι m
τ : Ω → WithTop ι
hτ : IsStoppingTime f τ
i : ι
hi : 0 ≤ i
j : ι
ω : Ω
⊢ ω ∈ {ω | τ ω + ↑i ≤ ↑j} ↔ ω ∈ {ω | τ ω ≤ ↑(j - i)}

Tactic:
simp only [Set.mem_ofPred_eq, coe_sub]

Goal state after:
Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝³ : AddGroup ι
inst✝² : Preorder ι
inst✝¹ : AddRightMono ι
inst✝ : AddLeftMono ι
f : Filtration ι m
τ : Ω → WithTop ι
hτ : IsStoppingTime f τ
i : ι
hi : 0 ≤ i
j : ι
ω : Ω
⊢ τ ω + ↑i ≤ ↑j ↔ τ ω ≤ ↑(j - i)
Module: Mathlib.Probability.Martingale.Convergence

Goal state before:
pp: Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
ℱ : Filtration ℕ m0
f : ℕ → Ω → ℝ
R : ℝ≥0
inst✝ : IsFiniteMeasure μ
hf : Submartingale f ℱ μ
hbdd : ∀ (n : ℕ), eLpNorm (f n) 1 μ ≤ ↑R
this : MeasurableSpace Ω := ⨆ n, ↑ℱ n
⊢ μ {a | ¬∃ c, Tendsto (fun n ↦ f n a) atTop (𝓝 c)} = 0

pp: case hs
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
ℱ : Filtration ℕ m0
f : ℕ → Ω → ℝ
R : ℝ≥0
inst✝ : IsFiniteMeasure μ
hf : Submartingale f ℱ μ
hbdd : ∀ (n : ℕ), eLpNorm (f n) 1 μ ≤ ↑R
this : MeasurableSpace Ω := ⨆ n, ↑ℱ n
⊢ MeasurableSet {a | ¬∃ c, Tendsto (fun n ↦ f n a) atTop (𝓝 c)}

Tactic:
· exact hf.exists_ae_tendsto_of_bdd hbdd

Goal state after:
case hs
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
ℱ : Filtration ℕ m0
f : ℕ → Ω → ℝ
R : ℝ≥0
inst✝ : IsFiniteMeasure μ
hf : Submartingale f ℱ μ
hbdd : ∀ (n : ℕ), eLpNorm (f n) 1 μ ≤ ↑R
this : MeasurableSpace Ω := ⨆ n, ↑ℱ n
⊢ MeasurableSet {a | ¬∃ c, Tendsto (fun n ↦ f n a) atTop (𝓝 c)}
Module: Mathlib.Probability.ConditionalExpectation

Goal state before:
pp: case pos.refine_2
Ω : Type u_1
E : Type u_2
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace ℝ E
inst✝¹ : CompleteSpace E
m₁ m₂ m : MeasurableSpace Ω
μ : Measure Ω
f : Ω → E
hle₁ : m₁ ≤ m
hle₂ : m₂ ≤ m
inst✝ : SigmaFinite (μ.trim hle₂)
hf : StronglyMeasurable f
hindp : Indep m₁ m₂ μ
hfint : MemLp f 1 μ
s : Set Ω
hms : MeasurableSet s
hs : μ s < ∞
c : E
t : Set Ω
⊢ MeasurableSet t →
    μ t < ∞ → μ.real s • ∫ (x : Ω), t.indicator (fun x ↦ c) x ∂μ = ∫ (x : Ω) in s, t.indicator (fun x ↦ c) x ∂μ

Tactic:
hmt

Goal state after:
case pos.refine_2
Ω : Type u_1
E : Type u_2
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace ℝ E
inst✝¹ : CompleteSpace E
m₁ m₂ m : MeasurableSpace Ω
μ : Measure Ω
f : Ω → E
hle₁ : m₁ ≤ m
hle₂ : m₂ ≤ m
inst✝ : SigmaFinite (μ.trim hle₂)
hf : StronglyMeasurable f
hindp : Indep m₁ m₂ μ
hfint : MemLp f 1 μ
s : Set Ω
hms : MeasurableSet s
hs : μ s < ∞
c : E
t : Set Ω
hmt : MeasurableSet t
⊢ μ t < ∞ → μ.real s • ∫ (x : Ω), t.indicator (fun x ↦ c) x ∂μ = ∫ (x : Ω) in s, t.indicator (fun x ↦ c) x ∂μ
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: Ω : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace Ω
inst✝¹ : Nonempty ι
u : ι → Ω → β
τ σ : Ω → WithTop ι
inst✝ : LinearOrder ι
μ : Measure Ω
hσ : ∀ᵐ (ω : Ω) ∂μ, σ ω ≠ ⊤
⊢ stoppedValue (stoppedProcess u τ) σ =ᵐ[μ] stoppedValue u fun ω ↦ min (σ ω) (τ ω)

Tactic:
by
  filter_upwards [hσ] with ω hσ using by simp [stoppedValue_stoppedProcess, hσ]

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

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
p : ℕ
⊢ centralMoment X p 0 = 0

Tactic:
simp [centralMoment]

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

Goal state before:
pp: case inl
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
inst✝ : IsZeroOrProbabilityMeasure 0
⊢ centralMoment X 1 0 = 0

Tactic:
simp [centralMoment]

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

Goal state before:
pp: case neg
Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝⁷ : Nonempty ι
τ : Ω → WithTop ι
inst✝⁶ : LinearOrder ι
inst✝⁵ : MeasurableSpace ι
inst✝⁴ : TopologicalSpace ι
inst✝³ : OrderTopology ι
inst✝² : SecondCountableTopology ι
inst✝¹ : BorelSpace ι
f : Filtration ι m
inst✝ : PseudoMetrizableSpace ι
hτ : IsStoppingTime f τ
i : ι
m_prod : MeasurableSpace (↑(Set.Iic i) × Ω) := Subtype.instMeasurableSpace.prod (↑f i)
m_set : (t : Set (↑(Set.Iic i) × Ω)) → MeasurableSpace ↑t := fun x ↦ Subtype.instMeasurableSpace
s : Set (↑(Set.Iic i) × Ω) := {p | τ p.2 ≤ ↑i}
hs : MeasurableSet s
h_meas_fst : ∀ (t : Set (↑(Set.Iic i) × Ω)), Measurable fun x ↦ ↑(↑x).1
sc : Set (↑(Set.Iic i) × Ω) := sᶜ
ω : ↑sc
hx_fst_le : ↑(↑ω).1 ≤ i
h : ¬τ (↑ω).2 = ⊤
⊢ ↑↑(↑ω).1 ≤ τ (↑ω).2

Tactic:
lift τ (ω : Set.Iic i × Ω).2 to ι using h with t ht
      norm_cast
      refine hx_fst_le.trans (le_of_lt ?_)
      convert! ω.prop
      simp only [sc, s, not_le, Set.mem_compl_iff, Set.mem_ofPred_eq, ← ht]
      norm_cast

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

Goal state before:
pp: Ω : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace Ω
inst✝⁸ : Nonempty ι
u : ι → Ω → β
τ : Ω → WithTop ι
inst✝⁷ : LinearOrder ι
inst✝⁶ : MeasurableSpace ι
inst✝⁵ : TopologicalSpace ι
inst✝⁴ : OrderTopology ι
inst✝³ : SecondCountableTopology ι
inst✝² : BorelSpace ι
inst✝¹ : TopologicalSpace β
f : Filtration ι m
inst✝ : PseudoMetrizableSpace ι
h : IsStronglyProgressive f u
hτ : IsStoppingTime f τ
⊢ IsStronglyProgressive f (MeasureTheory.stoppedProcess u τ)

Tactic:
have h_meas := isStronglyProgressive_min_stopping_time hτ
  refine h.comp h_meas fun i ω ↦ ?_
  cases τ ω with
  | top => simp
  | coe t =>
    rcases le_total i t with h_it | h_ti
    · simp [(mod_cast h_it : (i : WithTop ι) ≤ t)]
    · simpa [(mod_cast h_ti : t ≤ (i : WithTop ι))]

Goal state after:
Module: Mathlib.Probability.Martingale.BorelCantelli

Goal state before:
pp: case e'_1.refine_1
Ω : Type u_2
m0 : MeasurableSpace Ω
μ : Measure Ω
ℱ : Filtration ℕ m0
f : ℕ → Ω → ℝ
R : ℝ≥0
inst✝ : IsFiniteMeasure μ
hf : Submartingale f ℱ μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
g : ℕ → Ω → ℝ := fun n ω ↦ f n ω - f 0 ω
hg : Submartingale g ℱ μ
hg0 : g 0 = 0
hgbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |g (i + 1) ω - g i ω| ≤ ↑R
ω : Ω
hω : BddAbove (Set.range fun n ↦ g n ω) ↔ ∃ c, Tendsto (fun n ↦ g n ω) atTop (𝓝 c)
b : ℝ
hb : b ∈ upperBounds (Set.range fun n ↦ f n ω)
n : ℕ
⊢ (fun n ↦ g n ω) n ≤ b + |f 0 ω|

Tactic:
simp_rw [g, sub_eq_add_neg]
      exact add_le_add (hb ⟨n, rfl⟩) (neg_le_abs _)

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

Goal state before:
pp: Ω : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace Ω
inst✝¹⁰ : Nonempty ι
u : ι → Ω → β
τ : Ω → WithTop ι
inst✝⁹ : LinearOrder ι
inst✝⁸ : MeasurableSpace ι
inst✝⁷ : TopologicalSpace ι
inst✝⁶ : OrderTopology ι
inst✝⁵ : SecondCountableTopology ι
inst✝⁴ : BorelSpace ι
inst✝³ : TopologicalSpace β
f : Filtration ι m
inst✝² : PseudoMetrizableSpace β
inst✝¹ : MeasurableSpace β
inst✝ : BorelSpace β
hf_prog : IsStronglyProgressive f u
hτ : IsStoppingTime f τ
t : Set β
ht : MeasurableSet t
i : ι
h_str_meas : ∀ (i : ι), StronglyMeasurable (stoppedValue u fun ω ↦ min (τ ω) ↑i)
ω : Ω
h : τ ω ≤ ↑i
⊢ u (τ ω).untopA ω ∈ t ↔ u (min (τ ω) ↑i).untopA ω ∈ t

Tactic:
min_eq_left h

Goal state after:
Ω : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace Ω
inst✝¹⁰ : Nonempty ι
u : ι → Ω → β
τ : Ω → WithTop ι
inst✝⁹ : LinearOrder ι
inst✝⁸ : MeasurableSpace ι
inst✝⁷ : TopologicalSpace ι
inst✝⁶ : OrderTopology ι
inst✝⁵ : SecondCountableTopology ι
inst✝⁴ : BorelSpace ι
inst✝³ : TopologicalSpace β
f : Filtration ι m
inst✝² : PseudoMetrizableSpace β
inst✝¹ : MeasurableSpace β
inst✝ : BorelSpace β
hf_prog : IsStronglyProgressive f u
hτ : IsStoppingTime f τ
t : Set β
ht : MeasurableSet t
i : ι
h_str_meas : ∀ (i : ι), StronglyMeasurable (stoppedValue u fun ω ↦ min (τ ω) ↑i)
ω : Ω
h : τ ω ≤ ↑i
⊢ u (τ ω).untopA ω ∈ t ↔ u (τ ω).untopA ω ∈ t
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: Ω : Type u_1
β : Type u_2
u : ℕ → Ω → β
τ : Ω → ℕ∞
inst✝ : AddCommMonoid β
N : ℕ
ω : Ω
hbdd : τ ω ≤ ↑N
h_top : τ ω ≠ ⊤
⊢ τ ω ∈ WithTop.some '' ↑(Finset.range (N + 1))

Tactic:
lift τ ω to ℕ using h_top with t ht

Goal state after:
Ω : Type u_1
β : Type u_2
u : ℕ → Ω → β
τ : Ω → ℕ∞
inst✝ : AddCommMonoid β
N : ℕ
ω : Ω
t : ℕ
ht : ↑t = τ ω
hbdd : ↑t ≤ ↑N
⊢ ↑t ∈ WithTop.some '' ↑(Finset.range (N + 1))
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: case e_a.e_s
Ω : Type u_1
β : Type u_2
u : ℕ → Ω → β
τ : Ω → ℕ∞
inst✝ : AddCommMonoid β
n i : ℕ
⊢ i ∈ Finset.Iio n ↔ i ∈ Finset.range n

Tactic:
rw [Finset.mem_Iio, Finset.mem_range]

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

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t v x : ℝ
h_int_pos : Integrable (fun ω ↦ rexp ((v + t) * X ω)) μ
h_int_neg : Integrable (fun ω ↦ rexp ((v - t) * X ω)) μ
h_nonneg : 0 ≤ x
hx : x < |t|
n : ℕ
⊢ Integrable (fun a ↦ |X a| ^ n * rexp (v * X a + x * |X a|)) μ

Tactic:
convert!
    integrable_rpow_abs_mul_exp_add_of_integrable_exp_mul h_int_pos h_int_neg h_nonneg hx
      n.cast_nonneg
  simp

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

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t v : ℝ
ht : t ≠ 0
ht_int_pos : Integrable (fun ω ↦ rexp ((v + t) * X ω)) μ
ht_int_neg : Integrable (fun ω ↦ rexp ((v - t) * X ω)) μ
p : ℝ
hp : 0 ≤ p
⊢ Integrable (fun ω ↦ X ω ^ p * rexp (v * X ω)) μ

Tactic:
have hX : AEMeasurable X μ := aemeasurable_of_integrable_exp_mul ?_ ht_int_pos ht_int_neg
  swap; · rw [← sub_ne_zero]; simp [ht]
  rw [← integrable_norm_iff]
  · simp_rw [norm_eq_abs, abs_mul, abs_exp]
    have h := integrable_rpow_abs_mul_exp_of_integrable_exp_mul ht ht_int_pos ht_int_neg hp
    refine h.mono' ?_ ?_
    · fun_prop
    · refine ae_of_all _ fun ω ↦ ?_
      simp only [norm_mul, norm_eq_abs, abs_abs, abs_exp]
      gcongr
      exact abs_rpow_le_abs_rpow _ _
  · fun_prop

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

Goal state before:
pp: E : Type u_1
inst✝¹¹ : NormedAddCommGroup E
inst✝¹⁰ : InnerProductSpace ℝ E
inst✝⁹ : MeasurableSpace E
inst✝⁸ : BorelSpace E
μ : Measure E
F : Type u_2
inst✝⁷ : NormedAddCommGroup F
inst✝⁶ : InnerProductSpace ℝ F
inst✝⁵ : MeasurableSpace F
inst✝⁴ : BorelSpace F
inst✝³ : SecondCountableTopology F
inst✝² : CompleteSpace F
inst✝¹ : CompleteSpace E
inst✝ : IsFiniteMeasure μ
h : MemLp id 2 μ
L : E →L[ℝ] F
u v : F
⊢ ∫ (z : F),
      ⟪u, z - ∫ (x : F), id x ∂Measure.map (⇑L) μ⟫ * ⟪v, z - ∫ (x : F), id x ∂Measure.map (⇑L) μ⟫ ∂Measure.map (⇑L) μ =
    ∫ (z : E),
      ⟪(ContinuousLinearMap.adjoint L) u, z - ∫ (x : E), id x ∂μ⟫ *
        ⟪(ContinuousLinearMap.adjoint L) v, z - ∫ (x : E), id x ∂μ⟫ ∂μ

Tactic:
id,

Goal state after:
E : Type u_1
inst✝¹¹ : NormedAddCommGroup E
inst✝¹⁰ : InnerProductSpace ℝ E
inst✝⁹ : MeasurableSpace E
inst✝⁸ : BorelSpace E
μ : Measure E
F : Type u_2
inst✝⁷ : NormedAddCommGroup F
inst✝⁶ : InnerProductSpace ℝ F
inst✝⁵ : MeasurableSpace F
inst✝⁴ : BorelSpace F
inst✝³ : SecondCountableTopology F
inst✝² : CompleteSpace F
inst✝¹ : CompleteSpace E
inst✝ : IsFiniteMeasure μ
h : MemLp id 2 μ
L : E →L[ℝ] F
u v : F
⊢ ∫ (z : F), ⟪u, z - ∫ (x : F), x ∂Measure.map (⇑L) μ⟫ * ⟪v, z - ∫ (x : F), x ∂Measure.map (⇑L) μ⟫ ∂Measure.map (⇑L) μ =
    ∫ (z : E),
      ⟪(ContinuousLinearMap.adjoint L) u, z - ∫ (x : E), x ∂μ⟫ *
        ⟪(ContinuousLinearMap.adjoint L) v, z - ∫ (x : E), x ∂μ⟫ ∂μ
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: case neg.inr.inr
E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
p : ℝ≥0∞
c : E := ∫ (x : E), x ∂μ
h_Lp : MemLp (fun x ↦ x - c) p μ
this : id = fun x ↦ x - c + c
hx : ¬c = 0
hp0 : p ≠ 0
hptop : p ≠ ∞
I : Integrable (fun x ↦ ‖x‖) μ
⊢ Integrable (fun x ↦ ‖c‖ ^ p.toReal) μ

Tactic:
have := (h_Lp.integrable_norm_rpow hp0 hptop).const_mul (2 ^ p.toReal)

Goal state after:
case neg.inr.inr
E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
p : ℝ≥0∞
c : E := ∫ (x : E), x ∂μ
h_Lp : MemLp (fun x ↦ x - c) p μ
this✝ : id = fun x ↦ x - c + c
hx : ¬c = 0
hp0 : p ≠ 0
hptop : p ≠ ∞
I : Integrable (fun x ↦ ‖x‖) μ
this : Integrable (fun x ↦ 2 ^ p.toReal * ‖x - c‖ ^ p.toReal) μ
⊢ Integrable (fun x ↦ ‖c‖ ^ p.toReal) μ
Module: Mathlib.Probability.Distributions.Gaussian.CharFun

Goal state before:
pp: E : Type u_1
inst✝⁶ : NormedAddCommGroup E
inst✝⁵ : SecondCountableTopology E
inst✝⁴ : CompleteSpace E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : NormedSpace ℝ E
inst✝ : IsFiniteMeasure μ
x✝ : ∃ m f, f.toBilinForm.IsPosSemidef ∧ ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp (↑(L m) * I - ↑((f L) L) / 2)
m : E
f : StrongDual ℝ E →L[ℝ] StrongDual ℝ E →L[ℝ] ℝ
hf : f.toBilinForm.IsPosSemidef
h : ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp (↑(L m) * I - ↑((f L) L) / 2)
L : E →L[ℝ] ℝ
t : ℝ
⊢ cexp (↑((t • L) m) * I - ↑((f (t • L)) (t • L)) / 2) = cexp (↑t * ↑(L m) * I - ↑↑((f L) L).toNNReal * ↑t ^ 2 / 2)

Tactic:
smul_apply,

Goal state after:
E : Type u_1
inst✝⁶ : NormedAddCommGroup E
inst✝⁵ : SecondCountableTopology E
inst✝⁴ : CompleteSpace E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : NormedSpace ℝ E
inst✝ : IsFiniteMeasure μ
x✝ : ∃ m f, f.toBilinForm.IsPosSemidef ∧ ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp (↑(L m) * I - ↑((f L) L) / 2)
m : E
f : StrongDual ℝ E →L[ℝ] StrongDual ℝ E →L[ℝ] ℝ
hf : f.toBilinForm.IsPosSemidef
h : ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp (↑(L m) * I - ↑((f L) L) / 2)
L : E →L[ℝ] ℝ
t : ℝ
⊢ cexp (↑(t • L m) * I - ↑((f (t • L)) (t • L)) / 2) = cexp (↑t * ↑(L m) * I - ↑↑((f L) L).toNNReal * ↑t ^ 2 / 2)
Module: Mathlib.Probability.Distributions.Gaussian.CharFun

Goal state before:
pp: E : Type u_1
inst✝⁶ : NormedAddCommGroup E
inst✝⁵ : SecondCountableTopology E
inst✝⁴ : CompleteSpace E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : NormedSpace ℝ E
inst✝ : IsFiniteMeasure μ
x✝ : ∃ m f, f.toBilinForm.IsPosSemidef ∧ ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp (↑(L m) * I - ↑((f L) L) / 2)
m : E
f : StrongDual ℝ E →L[ℝ] StrongDual ℝ E →L[ℝ] ℝ
hf : f.toBilinForm.IsPosSemidef
h : ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp (↑(L m) * I - ↑((f L) L) / 2)
L : E →L[ℝ] ℝ
t : ℝ
⊢ cexp (↑(t • L m) * I - ↑(t • (t • f L) L) / 2) = cexp (↑t * ↑(L m) * I - ↑↑((f L) L).toNNReal * ↑t ^ 2 / 2)

Tactic:
smul_apply,

Goal state after:
E : Type u_1
inst✝⁶ : NormedAddCommGroup E
inst✝⁵ : SecondCountableTopology E
inst✝⁴ : CompleteSpace E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : NormedSpace ℝ E
inst✝ : IsFiniteMeasure μ
x✝ : ∃ m f, f.toBilinForm.IsPosSemidef ∧ ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp (↑(L m) * I - ↑((f L) L) / 2)
m : E
f : StrongDual ℝ E →L[ℝ] StrongDual ℝ E →L[ℝ] ℝ
hf : f.toBilinForm.IsPosSemidef
h : ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp (↑(L m) * I - ↑((f L) L) / 2)
L : E →L[ℝ] ℝ
t : ℝ
⊢ cexp (↑(t • L m) * I - ↑(t • t • (f L) L) / 2) = cexp (↑t * ↑(L m) * I - ↑↑((f L) L).toNNReal * ↑t ^ 2 / 2)
Module: Mathlib.Probability.BrownianMotion.GaussianProjectiveFamily

Goal state before:
pp: I : Finset ℝ≥0
f g : (↥I → ℝ) → ℝ
⊢ cov[f, g; projectiveFamily I] = cov[f ∘ ofLp, g ∘ ofLp; multivariateGaussian 0 (covMatrix I)]

Tactic:
by
  rw [projectiveFamily, covariance_map_equiv]
  rfl

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: case pos
E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
a : ℝ
inst✝ : IsProbabilityMeasure μ
h_rot : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
ha_pos : 0 < a
c' : ℝ≥0∞
hc' : c' ≤ μ {x | ‖x‖ ≤ a}
hc'_gt : 2⁻¹ < c'
t : ℕ → ℝ := normThreshold a
c : ℝ≥0∞ := μ {x | ‖x‖ ≤ a}
C : ℝ := logRatio c' * a⁻¹ ^ 2
hc'_le : c' ≤ 1
ha : ∀ᵐ (a_1 : E) ∂μ, ‖a_1‖ ≤ a
ht_int_zero : ∫⁻ (x : E) in closedBall 0 a, ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ ≤ ENNReal.ofReal (rexp (logRatio c'))
⊢ μ {x | x ∉ closedBall 0 a} = 0

Tactic:
rw [← ae_iff]

Goal state after:
case pos
E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
a : ℝ
inst✝ : IsProbabilityMeasure μ
h_rot : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
ha_pos : 0 < a
c' : ℝ≥0∞
hc' : c' ≤ μ {x | ‖x‖ ≤ a}
hc'_gt : 2⁻¹ < c'
t : ℕ → ℝ := normThreshold a
c : ℝ≥0∞ := μ {x | ‖x‖ ≤ a}
C : ℝ := logRatio c' * a⁻¹ ^ 2
hc'_le : c' ≤ 1
ha : ∀ᵐ (a_1 : E) ∂μ, ‖a_1‖ ≤ a
ht_int_zero : ∫⁻ (x : E) in closedBall 0 a, ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ ≤ ENNReal.ofReal (rexp (logRatio c'))
⊢ ∀ᵐ (a_1 : E) ∂μ, a_1 ∈ closedBall 0 a
Module: Mathlib.Probability.Independence.Process.Basic

Goal state before:
pp: S : Type u_1
Ω : Type u_3
mΩ : MeasurableSpace Ω
α : Type u_4
mα : MeasurableSpace α
κ : Kernel α Ω
P : Measure α
T : S → Type u_5
𝓧 : (i : S) → T i → Type u_6
inst✝ : (i : S) → (j : T i) → MeasurableSpace (𝓧 i j)
X X' : (i : S) → (j : T i) → Ω → 𝓧 i j
h1 : iIndepFun (fun i ω j ↦ X i j ω) κ P
h2 : ∀ (i : S) (j : T i), ∀ᵐ (a : α) ∂P, X i j =ᵐ[κ a] X' i j
s : Finset S
f✝ : S → Set Ω
g : (i : S) → Set ((fun i ↦ (j : T i) → 𝓧 i j) i)
mg : ∀ i ∈ s, MeasurableSet (g i)
hg : ∀ i ∈ s, (fun i ω j ↦ X' i j ω) i ⁻¹' g i = f✝ i
h3 : ⋂ i ∈ s, f✝ i = ⋂ i ∈ s, (fun i ω j ↦ X' i j ω) i ⁻¹' g i
h3' : ∀ (a : α), ∏ i ∈ s, (κ a) (f✝ i) = ∏ i ∈ s, (κ a) ((fun i ω j ↦ X' i j ω) i ⁻¹' g i)
I : (i : S) → Set (T i)
u : (i : S) → Set ((a : ↑(I i)) → 𝓧 i ↑a)
hI : ∀ i ∈ s, (I i).Countable
hu : ∀ i ∈ s, g i = (I i).domRestrict ⁻¹' u i
f : (i : S) → (j : T i) → Ω → 𝓧 i j
i : S
hi : i ∈ s
⊢ (fun i ω j ↦ f i j ω) i ⁻¹' (I i).domRestrict ⁻¹' u i = (fun i ω j ↦ f i j ω) i ⁻¹' g i

Tactic:
hu i hi

Goal state after:
S : Type u_1
Ω : Type u_3
mΩ : MeasurableSpace Ω
α : Type u_4
mα : MeasurableSpace α
κ : Kernel α Ω
P : Measure α
T : S → Type u_5
𝓧 : (i : S) → T i → Type u_6
inst✝ : (i : S) → (j : T i) → MeasurableSpace (𝓧 i j)
X X' : (i : S) → (j : T i) → Ω → 𝓧 i j
h1 : iIndepFun (fun i ω j ↦ X i j ω) κ P
h2 : ∀ (i : S) (j : T i), ∀ᵐ (a : α) ∂P, X i j =ᵐ[κ a] X' i j
s : Finset S
f✝ : S → Set Ω
g : (i : S) → Set ((fun i ↦ (j : T i) → 𝓧 i j) i)
mg : ∀ i ∈ s, MeasurableSet (g i)
hg : ∀ i ∈ s, (fun i ω j ↦ X' i j ω) i ⁻¹' g i = f✝ i
h3 : ⋂ i ∈ s, f✝ i = ⋂ i ∈ s, (fun i ω j ↦ X' i j ω) i ⁻¹' g i
h3' : ∀ (a : α), ∏ i ∈ s, (κ a) (f✝ i) = ∏ i ∈ s, (κ a) ((fun i ω j ↦ X' i j ω) i ⁻¹' g i)
I : (i : S) → Set (T i)
u : (i : S) → Set ((a : ↑(I i)) → 𝓧 i ↑a)
hI : ∀ i ∈ s, (I i).Countable
hu : ∀ i ∈ s, g i = (I i).domRestrict ⁻¹' u i
f : (i : S) → (j : T i) → Ω → 𝓧 i j
i : S
hi : i ∈ s
⊢ (fun i ω j ↦ f i j ω) i ⁻¹' (I i).domRestrict ⁻¹' u i = (fun i ω j ↦ f i j ω) i ⁻¹' (I i).domRestrict ⁻¹' u i
Module: Mathlib.Probability.Independence.Process.Basic

Goal state before:
pp: S : Type u_1
Ω : Type u_3
mΩ : MeasurableSpace Ω
α : Type u_4
mα : MeasurableSpace α
κ : Kernel α Ω
P : Measure α
T : S → Type u_5
𝓧 : (i : S) → T i → Type u_6
inst✝ : (i : S) → (j : T i) → MeasurableSpace (𝓧 i j)
X X' : (i : S) → (j : T i) → Ω → 𝓧 i j
h1 : iIndepFun (fun i ω j ↦ X i j ω) κ P
h2 : ∀ (i : S) (j : T i), ∀ᵐ (a : α) ∂P, X i j =ᵐ[κ a] X' i j
s : Finset S
f✝ : S → Set Ω
g : (i : S) → Set ((fun i ↦ (j : T i) → 𝓧 i j) i)
mg : ∀ i ∈ s, MeasurableSet (g i)
hg : ∀ i ∈ s, (fun i ω j ↦ X' i j ω) i ⁻¹' g i = f✝ i
h3 : ⋂ i ∈ s, f✝ i = ⋂ i ∈ s, (fun i ω j ↦ X' i j ω) i ⁻¹' g i
h3' : ∀ (a : α), ∏ i ∈ s, (κ a) (f✝ i) = ∏ i ∈ s, (κ a) ((fun i ω j ↦ X' i j ω) i ⁻¹' g i)
I : (i : S) → Set (T i)
u : (i : S) → Set ((a : ↑(I i)) → 𝓧 i ↑a)
hI : ∀ i ∈ s, (I i).Countable
hu : ∀ i ∈ s, g i = (I i).domRestrict ⁻¹' u i
h4 :
  ∀ (f : (i : S) → (j : T i) → Ω → 𝓧 i j),
    ⋂ i ∈ s, (fun i ω j ↦ f i j ω) i ⁻¹' g i = ⋂ i ∈ s, (fun i ω j ↦ f i j ω) i ⁻¹' (I i).domRestrict ⁻¹' u i
a : α
f : (i : S) → (j : T i) → Ω → 𝓧 i j
i : S
hi : i ∈ s
⊢ (κ a) ((fun i ω j ↦ f i j ω) i ⁻¹' g i) = (κ a) ((fun i ω j ↦ f i j ω) i ⁻¹' (I i).domRestrict ⁻¹' u i)

Tactic:
hu i hi

Goal state after:
S : Type u_1
Ω : Type u_3
mΩ : MeasurableSpace Ω
α : Type u_4
mα : MeasurableSpace α
κ : Kernel α Ω
P : Measure α
T : S → Type u_5
𝓧 : (i : S) → T i → Type u_6
inst✝ : (i : S) → (j : T i) → MeasurableSpace (𝓧 i j)
X X' : (i : S) → (j : T i) → Ω → 𝓧 i j
h1 : iIndepFun (fun i ω j ↦ X i j ω) κ P
h2 : ∀ (i : S) (j : T i), ∀ᵐ (a : α) ∂P, X i j =ᵐ[κ a] X' i j
s : Finset S
f✝ : S → Set Ω
g : (i : S) → Set ((fun i ↦ (j : T i) → 𝓧 i j) i)
mg : ∀ i ∈ s, MeasurableSet (g i)
hg : ∀ i ∈ s, (fun i ω j ↦ X' i j ω) i ⁻¹' g i = f✝ i
h3 : ⋂ i ∈ s, f✝ i = ⋂ i ∈ s, (fun i ω j ↦ X' i j ω) i ⁻¹' g i
h3' : ∀ (a : α), ∏ i ∈ s, (κ a) (f✝ i) = ∏ i ∈ s, (κ a) ((fun i ω j ↦ X' i j ω) i ⁻¹' g i)
I : (i : S) → Set (T i)
u : (i : S) → Set ((a : ↑(I i)) → 𝓧 i ↑a)
hI : ∀ i ∈ s, (I i).Countable
hu : ∀ i ∈ s, g i = (I i).domRestrict ⁻¹' u i
h4 :
  ∀ (f : (i : S) → (j : T i) → Ω → 𝓧 i j),
    ⋂ i ∈ s, (fun i ω j ↦ f i j ω) i ⁻¹' g i = ⋂ i ∈ s, (fun i ω j ↦ f i j ω) i ⁻¹' (I i).domRestrict ⁻¹' u i
a : α
f : (i : S) → (j : T i) → Ω → 𝓧 i j
i : S
hi : i ∈ s
⊢ (κ a) ((fun i ω j ↦ f i j ω) i ⁻¹' (I i).domRestrict ⁻¹' u i) =
    (κ a) ((fun i ω j ↦ f i j ω) i ⁻¹' (I i).domRestrict ⁻¹' u i)