mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N : ℕ
ω : Ω
hab : a < b
⊢ upcrossingsBefore 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N ω = upcrossingsBefore a b f N ω

Tactic:
upcrossingsBefore,

Goal state after:
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N : ℕ
ω : Ω
hab : a < b
⊢ sSup {n | upperCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N n ω < N} =
    sSup {n | upperCrossingTime a b f N n ω < N}
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
ω : Ω
⊢ upcrossings a b f ω < ∞ ↔ ∃ k, ∀ (N : ℕ), upcrossingsBefore a b f N ω ≤ k

Tactic:
have : upcrossings a b f ω < ∞ ↔ ∃ k : ℝ≥0, upcrossings a b f ω ≤ k := by
    constructor
    · intro h
      lift upcrossings a b f ω to ℝ≥0 using h.ne with r hr
      exact ⟨r, le_rfl⟩
    · rintro ⟨k, hk⟩
      exact lt_of_le_of_lt hk ENNReal.coe_lt_top
  simp_rw [this, upcrossings, iSup_le_iff]
  constructor <;> rintro ⟨k, hk⟩
  · obtain ⟨m, hm⟩ := exists_nat_ge k
    refine ⟨m, fun N => Nat.cast_le.1 ((hk N).trans ?_)⟩
    rwa [← ENNReal.coe_natCast, ENNReal.coe_le_coe]
  · refine ⟨k, fun N => ?_⟩
    simp only [ENNReal.coe_natCast, Nat.cast_le, hk N]

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

Goal state before:
pp: case hs
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
𝒢 : Filtration ℕ m0
f : ℕ → Ω → ℝ
inst✝ : IsFiniteMeasure μ
hsub : Submartingale f 𝒢 μ
hnonneg : 0 ≤ f
ε : ℝ≥0
n : ℕ
⊢ NullMeasurableSet {ω | ((range (n + 1)).sup' ⋯ fun k ↦ f k ω) < ↑ε} μ

Tactic:
exact nullMeasurableSet_lt (measurable_range_sup'' fun n _ ↦
          (hsub.stronglyMeasurable n).measurable.le (𝒢.le n)).aemeasurable aemeasurable_const

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

Goal state before:
pp: 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
h_min_eq_left : (fun x ↦ min (↑↑(↑x).1) (τ (↑x).2)) = fun x ↦ ↑↑(↑x).1
⊢ Measurable (sᶜ.domRestrict fun p ↦ min (↑↑p.1) (τ p.2))

Tactic:
simp +unfoldPartialApp only [sc, Set.domRestrict, h_min_eq_left]
      exact (h_meas_fst _).withTop_coe

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

Goal state before:
pp: 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 : Martingale f ℱ μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
ω : Ω
hω : ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
i : ℕ
⊢ |(-f) (i + 1) ω - (-f) i ω| ≤ ↑R

Tactic:
simp only [Pi.neg_apply]

Goal state after:
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 : Martingale f ℱ μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
ω : Ω
hω : ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
i : ℕ
⊢ |-f (i + 1) ω - -f i ω| ≤ ↑R
Module: Mathlib.Probability.Martingale.BorelCantelli

Goal state before:
pp: 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 : Martingale f ℱ μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
hbdd' : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |(-f) (i + 1) ω - (-f) i ω| ≤ ↑R
hup : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hdown : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
ω : Ω
hω₁ : BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hω₂ : BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
⊢ (∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)

Tactic:
constructor <;> rintro ⟨c, hc⟩

Goal state after:
case mp
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 : Martingale f ℱ μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
hbdd' : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |(-f) (i + 1) ω - (-f) i ω| ≤ ↑R
hup : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hdown : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
ω : Ω
hω₁ : BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hω₂ : BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
c : ℝ
hc : Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
⊢ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)

case mpr
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 : Martingale f ℱ μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
hbdd' : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |(-f) (i + 1) ω - (-f) i ω| ≤ ↑R
hup : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hdown : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
ω : Ω
hω₁ : BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hω₂ : BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
c : ℝ
hc : Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
⊢ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
Module: Mathlib.Probability.BorelCantelli

Goal state before:
pp: case refine_2
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
s : ℕ → Set Ω
hsm : ∀ (n : ℕ), MeasurableSet (s n)
hs : iIndepSet s μ
hs' : ∑' (n : ℕ), μ (s n) = ∞
this✝ : IsProbabilityMeasure μ
this :
  ∀ᵐ (ω : Ω) ∂μ, ∀ (n : ℕ), μ[(s (n + 1)).indicator 1 | ↑(filtrationOfSet hsm) n] ω = (fun x ↦ μ.real (s (n + 1))) ω
ω : Ω
hω : ∀ (n : ℕ), μ[(s (n + 1)).indicator 1 | ↑(filtrationOfSet hsm) n] ω = μ.real (s (n + 1))
htends : ∀ (x : NNReal), ∀ᶠ (a : ℕ) in atTop, ↑x < ∑ k ∈ Finset.range a, μ (s (k + 1))
B : ℝ
n : ℕ
hB : (∑ k ∈ Finset.range n, μ (s (k + 1))).toReal ≤ B
⊢ ¬↑B.toNNReal < ∑ k ∈ Finset.range n, μ (s (k + 1))

Tactic:
rwa [not_lt, ENNReal.ofNNReal_toNNReal, ENNReal.le_ofReal_iff_toReal_le]
      · simp
      · exact le_trans (by positivity) hB

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

Goal state before:
pp: case refine_2
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
h_str_meas : ∀ (i : ι), StronglyMeasurable (stoppedValue u fun ω ↦ min (τ ω) ↑i)
t : Set β
ht : MeasurableSet t
seq : ℕ → ι
h_seq_tendsto : Tendsto seq atTop atTop
this :
  stoppedValue u τ ⁻¹' t = (⋃ n, stoppedValue u τ ⁻¹' t ∩ {ω | τ ω ≤ ↑(seq n)}) ∪ stoppedValue u τ ⁻¹' t ∩ {ω | τ ω = ⊤}
⊢ MeasurableSet (stoppedValue u τ ⁻¹' t ∩ {ω | τ ω = ⊤})

Tactic:
have : stoppedValue u τ ⁻¹' t ∩ {ω | τ ω = ⊤}
       = (fun ω ↦ u (Classical.arbitrary ι) ω) ⁻¹' t ∩ {ω | τ ω = ⊤} := by
      ext ω
      simp only [Set.mem_inter_iff, Set.mem_preimage, stoppedValue, untopA,
        Set.mem_ofPred_eq, and_congr_left_iff]
      intro h
      simp [h]
    rw [this]
    refine MeasurableSet.inter (ht.preimage ?_) hτ.measurableSet_eq_top'
    exact (hf_prog.stronglyAdapted (Classical.arbitrary ι)).measurable.mono
      (le_iSup f (Classical.arbitrary ι)) le_rfl

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

Goal state before:
pp: 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 : Martingale f ℱ μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
hbdd' : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |(-f) (i + 1) ω - (-f) i ω| ≤ ↑R
hup : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hdown : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
ω : Ω
hω₁ : BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hω₂ : BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
this : (∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
⊢ BddAbove (Set.range fun n ↦ (-f) n ω) ↔ BddBelow (Set.range fun n ↦ f n ω)

Tactic:
constructor <;> rintro ⟨c, hc⟩

Goal state after:
case mp
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 : Martingale f ℱ μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
hbdd' : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |(-f) (i + 1) ω - (-f) i ω| ≤ ↑R
hup : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hdown : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
ω : Ω
hω₁ : BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hω₂ : BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
this : (∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
c : ℝ
hc : c ∈ upperBounds (Set.range fun n ↦ (-f) n ω)
⊢ BddBelow (Set.range fun n ↦ f n ω)

case mpr
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 : Martingale f ℱ μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |f (i + 1) ω - f i ω| ≤ ↑R
hbdd' : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |(-f) (i + 1) ω - (-f) i ω| ≤ ↑R
hup : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hdown : ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
ω : Ω
hω₁ : BddAbove (Set.range fun n ↦ f n ω) ↔ ∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)
hω₂ : BddAbove (Set.range fun n ↦ (-f) n ω) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
this : (∃ c, Tendsto (fun n ↦ f n ω) atTop (𝓝 c)) ↔ ∃ c, Tendsto (fun n ↦ (-f) n ω) atTop (𝓝 c)
c : ℝ
hc : c ∈ lowerBounds (Set.range fun n ↦ f n ω)
⊢ BddAbove (Set.range fun n ↦ (-f) n ω)
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: Ω : Type u_1
ι : Type u_3
inst✝² : Nonempty ι
τ : Ω → WithTop ι
E : Type u_4
u : ι → Ω → E
inst✝¹ : LinearOrder ι
inst✝ : AddCommMonoid E
s : Finset ι
n : ι
hbdd : ∀ (ω : Ω), τ ω < ↑n → τ ω ∈ WithTop.some '' ↑s
⊢ stoppedProcess u τ n = {a | ↑n ≤ τ a}.indicator (u n) + ∑ i ∈ s with i < n, {ω | τ ω = ↑i}.indicator (u i)

Tactic:
ext ω
  rw [Pi.add_apply, Finset.sum_apply]
  rcases le_or_gt (n : WithTop ι) (τ ω) with h | h
  · rw [stoppedProcess_eq_of_le h, Set.indicator_of_mem, Finset.sum_eq_zero, add_zero]
    · intro m hm
      refine Set.indicator_of_notMem ?_ _
      rw [Finset.mem_filter] at hm
      simp only [Set.mem_ofPred_eq]
      refine (lt_of_lt_of_le ?_ h).ne'
      exact mod_cast hm.2
    · exact h
  · rw [stoppedProcess_eq_of_ge (le_of_lt h)]
    have h_top : τ ω ≠ ⊤ := fun h_contra ↦ by simp [h_contra] at h
    specialize hbdd ω h
    lift τ ω to ι using h_top with i hi
    rw [Finset.sum_eq_single_of_mem i]
    · simp only [untopD_coe]
      rw [Set.indicator_of_notMem, zero_add, Set.indicator_of_mem] <;> rw [Set.mem_ofPred]
      · exact hi.symm
      · rw [← hi]
        exact not_le.2 h
    · rw [Finset.mem_filter]
      simp only [Set.mem_image, Finset.mem_coe, coe_eq_coe, exists_eq_right] at hbdd
      exact ⟨hbdd, mod_cast h⟩
    · intro b _ hneq
      rw [Set.indicator_of_notMem]
      rw [Set.mem_ofPred, ← hi]
      exact mod_cast hneq.symm

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

Goal state before:
pp: case inr
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t v : ℝ
ht_int_pos : Integrable (fun ω ↦ rexp ((v + t) * X ω)) μ
ht_int_neg : Integrable (fun ω ↦ rexp ((v - t) * X ω)) μ
ht_nonpos : t ≤ 0
⊢ Integrable (fun ω ↦ rexp (|t| * |X ω| + v * X ω)) μ

Tactic:
simp_rw [abs_of_nonpos ht_nonpos]

Goal state after:
case inr
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t v : ℝ
ht_int_pos : Integrable (fun ω ↦ rexp ((v + t) * X ω)) μ
ht_int_neg : Integrable (fun ω ↦ rexp ((v - t) * X ω)) μ
ht_nonpos : t ≤ 0
⊢ Integrable (fun ω ↦ rexp (-t * |X ω| + v * X ω)) μ
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: case inr
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t : ℝ
ht_int_pos : Integrable (fun ω ↦ rexp (t * X ω)) μ
ht_int_neg : Integrable (fun ω ↦ rexp (-t * X ω)) μ
ht_nonpos : t ≤ 0
⊢ Integrable (fun ω ↦ rexp (|t| * |X ω|)) μ

Tactic:
simp_rw [abs_of_nonpos ht_nonpos]

Goal state after:
case inr
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t : ℝ
ht_int_pos : Integrable (fun ω ↦ rexp (t * X ω)) μ
ht_int_neg : Integrable (fun ω ↦ rexp (-t * X ω)) μ
ht_nonpos : t ≤ 0
⊢ Integrable (fun ω ↦ rexp (-t * |X ω|)) μ
Module: Mathlib.Probability.Moments.ComplexMGF

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
z : ℂ
⊢ ‖∫ (ω : Ω), cexp ((↑z.re + ↑z.im * I) * ↑(X ω)) ∂μ‖ ≤ mgf X μ (↑z.re + ↑z.im * I).re

Tactic:
add_mul,

Goal state after:
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
z : ℂ
⊢ ‖∫ (ω : Ω), cexp (↑z.re * ↑(X ω) + ↑z.im * I * ↑(X ω)) ∂μ‖ ≤ mgf X μ (↑z.re + ↑z.im * I).re
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: case hbc
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|
p : ℝ
hp : 0 ≤ p
ht : t ≠ 0
hX : AEMeasurable X μ
a : Ω
this : |t| = |t| - x + x
⊢ |X a| ^ p * rexp (x * |X a|) ≤ (p / (|t| - x)) ^ p * rexp ((|t| - x + x) * |X a|)

Tactic:
add_mul,

Goal state after:
case hbc
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|
p : ℝ
hp : 0 ≤ p
ht : t ≠ 0
hX : AEMeasurable X μ
a : Ω
this : |t| = |t| - x + x
⊢ |X a| ^ p * rexp (x * |X a|) ≤ (p / (|t| - x)) ^ p * rexp ((|t| - x) * |X a| + x * |X a|)
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: case refine_2.refine_3.e_a
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|
p : ℝ
hp : 0 ≤ p
ht : t ≠ 0
hX : AEMeasurable X μ
h_le : ∀ (a : Ω), |X a| ^ p * rexp (v * X a + x * |X a|) ≤ (p / (|t| - x)) ^ p * rexp (v * X a + |t| * |X a|)
ω : Ω
⊢ 0 ≤ (p / (|t| - x)) ^ p

Tactic:
positivity [sub_nonneg_of_le hx.le]

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Real

Goal state before:
pp: case hfi
μ : ℝ
v : ℝ≥0
hv : v ≠ 0
s : Set ℝ
⊢ Integrable (gaussianPDFReal μ v) (ℙ.restrict s)

Tactic:
exact (integrable_gaussianPDFReal _ _).restrict

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

Goal state before:
pp: case e_a
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
v : ℝ
h : v ∈ interior (integrableExpSet X μ)
hμ : ¬μ = 0
⊢ ∫ (ω : Ω), X ω ^ 2 * rexp (v * X ω) ∂μ - (2 * ∫ (ω : Ω), X ω * rexp (v * X ω) ∂μ) * deriv (cgf X μ) v +
      deriv (cgf X μ) v ^ 2 * mgf X μ v =
    ∫ (ω : Ω), (X ω ^ 2 - 2 * X ω * deriv (cgf X μ) v + deriv (cgf X μ) v ^ 2) * rexp (v * X ω) ∂μ

Tactic:
add_mul,

Goal state after:
case e_a
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
v : ℝ
h : v ∈ interior (integrableExpSet X μ)
hμ : ¬μ = 0
⊢ ∫ (ω : Ω), X ω ^ 2 * rexp (v * X ω) ∂μ - (2 * ∫ (ω : Ω), X ω * rexp (v * X ω) ∂μ) * deriv (cgf X μ) v +
      deriv (cgf X μ) v ^ 2 * mgf X μ v =
    ∫ (ω : Ω), (X ω ^ 2 - 2 * X ω * deriv (cgf X μ) v) * rexp (v * X ω) + deriv (cgf X μ) v ^ 2 * rexp (v * X ω) ∂μ
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: m : ℝ
v : ℝ≥0
L : StrongDual ℝ ℝ
⊢ gaussianReal (L m) ((L 1 ^ 2).toNNReal * v) =
    gaussianReal (∫ (x : ℝ), L x ∂gaussianReal m v) Var[⇑L; gaussianReal m v].toNNReal

Tactic:
simp only [integral_continuousLinearMap_gaussianReal, variance_continuousLinearMap_gaussianReal,
      Real.coe_toNNReal']

Goal state after:
m : ℝ
v : ℝ≥0
L : StrongDual ℝ ℝ
⊢ gaussianReal (L m) ((L 1 ^ 2).toNNReal * v) = gaussianReal (L m) (max (L 1 ^ 2) 0 * ↑v).toNNReal
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: case neg
E : Type u_1
inst✝³ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
p : ℝ≥0∞
𝕜 : Type u_2
inst✝² : NontriviallyNormedField 𝕜
inst✝¹ : NormedSpace 𝕜 E
inst✝ : OpensMeasurableSpace E
L : StrongDual 𝕜 E
h_Lp : MemLp id p μ
hp : ¬p = 0
hp_top : ¬p = ∞
h0 : 0 < p.toReal
⊢ ‖(toLpₗ μ p) L‖ ≤ ‖L‖ * (eLpNorm id p μ).toReal

Tactic:
suffices ‖L.toLpₗ μ p‖
      ≤ (‖L‖ₑ ^ p.toReal * ∫⁻ x, ‖x‖ₑ ^ p.toReal ∂μ).toReal ^ p.toReal⁻¹ by
    refine this.trans_eq ?_
    simp only [ENNReal.toReal_mul]
    rw [← ENNReal.toReal_rpow, Real.mul_rpow (by positivity) (by positivity),
      ← Real.rpow_mul (by positivity), mul_inv_cancel₀ h0.ne', Real.rpow_one, toReal_enorm]
    rw [eLpNorm_eq_lintegral_rpow_enorm_toReal (by simp [hp]) hp_top, ENNReal.toReal_rpow]
    simp

Goal state after:
case neg
E : Type u_1
inst✝³ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
p : ℝ≥0∞
𝕜 : Type u_2
inst✝² : NontriviallyNormedField 𝕜
inst✝¹ : NormedSpace 𝕜 E
inst✝ : OpensMeasurableSpace E
L : StrongDual 𝕜 E
h_Lp : MemLp id p μ
hp : ¬p = 0
hp_top : ¬p = ∞
h0 : 0 < p.toReal
⊢ ‖(toLpₗ μ p) L‖ ≤ (‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ).toReal ^ p.toReal⁻¹
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝³ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
p : ℝ≥0∞
𝕜 : Type u_2
inst✝² : NontriviallyNormedField 𝕜
inst✝¹ : NormedSpace 𝕜 E
inst✝ : OpensMeasurableSpace E
L : StrongDual 𝕜 E
h_Lp : MemLp id p μ
hp : ¬p = 0
hp_top : ¬p = ∞
h0 : 0 < p.toReal
this : ∫⁻ (x : E), ‖L x‖ₑ ^ p.toReal ∂μ ≤ ‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ
⊢ (∫⁻ (x : E), ‖L x‖ₑ ^ p.toReal ∂μ) ^ p.toReal⁻¹ ≤
    ENNReal.ofReal ((‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ).toReal ^ p.toReal⁻¹)

Tactic:
← ENNReal.ofReal_rpow_of_nonneg (by positivity) (by positivity)

Goal state after:
E : Type u_1
inst✝³ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
p : ℝ≥0∞
𝕜 : Type u_2
inst✝² : NontriviallyNormedField 𝕜
inst✝¹ : NormedSpace 𝕜 E
inst✝ : OpensMeasurableSpace E
L : StrongDual 𝕜 E
h_Lp : MemLp id p μ
hp : ¬p = 0
hp_top : ¬p = ∞
h0 : 0 < p.toReal
this : ∫⁻ (x : E), ‖L x‖ₑ ^ p.toReal ∂μ ≤ ‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ
⊢ (∫⁻ (x : E), ‖L x‖ₑ ^ p.toReal ∂μ) ^ p.toReal⁻¹ ≤
    ENNReal.ofReal (‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ).toReal ^ p.toReal⁻¹
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: 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
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ MeasurableSet {p | ‖p.1‖ ≤ a ∧ b < ‖p.2‖}

pp: 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
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ (μ.prod μ) (⇑(ContinuousLinearMap.rotation (-(π / 4))) ⁻¹' {p | ‖p.1‖ ≤ a ∧ b < ‖p.2‖}) =
    (μ.prod μ) {p | ‖p.1 - p.2‖ / √2 ≤ a ∧ b < ‖p.1 + p.2‖ / √2}

Tactic:
· refine MeasurableSet.inter ?_ ?_
      · change MeasurableSet {p : E × E | ‖p.1‖ ≤ a}
        exact measurableSet_le (by fun_prop) (by fun_prop)
      · change MeasurableSet {p : E × E | b < ‖p.2‖}
        exact measurableSet_lt (by fun_prop) (by fun_prop)

Goal state after:
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
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ (μ.prod μ) (⇑(ContinuousLinearMap.rotation (-(π / 4))) ⁻¹' {p | ‖p.1‖ ≤ a ∧ b < ‖p.2‖}) =
    (μ.prod μ) {p | ‖p.1 - p.2‖ / √2 ≤ a ∧ b < ‖p.1 + p.2‖ / √2}
Module: Mathlib.Probability.Distributions.Gaussian.CharFun

Goal state before:
pp: case h
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✝ : IsGaussian μ
L : StrongDual ℝ E
⊢ MemLp id 2 μ

Tactic:
exact IsGaussian.memLp_two_id

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

Goal state before:
pp: a : ℝ
n : ℕ
⊢ normThreshold a n = a * (1 + √2) * (√2 ^ (n + 1) - 1)

Tactic:
rw [normThreshold, arithGeom_same_eq_mul_div (by simp), div_eq_mul_inv, Real.inv_sqrt_two_sub_one]
  ring

Goal state after:
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✝ : IsGaussian μ
L : StrongDual ℝ E
⊢ charFunDual μ L = cexp (↑(L (∫ (x : E), id x ∂μ)) * I - ↑(((covarianceBilinDual μ) L) L) / 2)

Tactic:
by
  rw [IsGaussian.charFunDual_eq, covarianceBilinDual_self_eq_variance, integral_complex_ofReal,
    L.integral_comp_id_comm']
  · exact IsGaussian.integrable_id
  · exact IsGaussian.memLp_two_id

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

Goal state before:
pp: E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
c : E := ∫ (x : E), x ∂μ
this✝¹ : id = fun x ↦ x - c + c
hx : ¬c = 0
I : Integrable (fun x ↦ ‖x‖) μ
y : E
p : ℝ≥0
h_Lp : MemLp (fun x ↦ x - c) (↑p) μ
hp0 : ↑p ≠ 0
this✝ : Integrable (fun x ↦ 2 ^ (↑p).toReal * ‖x - c‖ ^ (↑p).toReal) μ
h✝ : ‖y‖ ≤ ‖c‖ / 2
this : ‖c‖ ≤ ‖y‖ + ‖y - c‖
⊢ (2 * ‖y - c‖) ^ ↑p = 0 + 2 ^ ↑p * ‖y - c‖ ^ ↑p

Tactic:
by
      rw [Real.mul_rpow (by simp) (by positivity)]
      ring

Goal state after: