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 i : ι
ω : Ω
h' : hittingAfter u s n ω < ↑i
h : hittingAfter u s n ω = ⊤
⊢ False

Tactic:
simp [h] at h'

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

Goal state before:
pp: Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝³ : LinearOrder ι
f : Filtration ι m
τ : Ω → WithTop ι
inst✝² : TopologicalSpace ι
inst✝¹ : OrderTopology ι
inst✝ : FirstCountableTopology ι
hτ : IsStoppingTime f τ
i : ι
this : {ω | τ ω = ↑i} = {ω | τ ω ≤ ↑i} ∩ {ω | τ ω ≥ ↑i}
⊢ MeasurableSet ({ω | τ ω ≤ ↑i} ∩ {ω | τ ω ≥ ↑i})

Tactic:
exact (hτ.measurableSet_le i).inter (hτ.measurableSet_ge i)

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

Goal state before:
pp: Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
ℱ : Filtration ℕ m0
inst✝ : IsFiniteMeasure μ
hf : Submartingale f ℱ μ
h₁ :
  ∫ (x : Ω), (∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)) x ∂μ ≤
    ∫ (x : Ω), (∑ k ∈ Finset.range n, (f (k + 1) - f k)) x ∂μ
h₂ :
  ∫ (x : Ω), (∑ k ∈ Finset.range n, (1 - upcrossingStrat a b f N k) * (f (k + 1) - f k)) x ∂μ =
    ∫ (x : Ω), (∑ k ∈ Finset.range n, (f (k + 1) - f k)) x ∂μ -
      ∫ (x : Ω), (∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)) x ∂μ
⊢ ∫ (x : Ω), (∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)) x ∂μ ≤
    ∫ (x : Ω), f n x ∂μ - ∫ (x : Ω), f 0 x ∂μ

Tactic:
refine le_trans h₁ ?_

Goal state after:
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
ℱ : Filtration ℕ m0
inst✝ : IsFiniteMeasure μ
hf : Submartingale f ℱ μ
h₁ :
  ∫ (x : Ω), (∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)) x ∂μ ≤
    ∫ (x : Ω), (∑ k ∈ Finset.range n, (f (k + 1) - f k)) x ∂μ
h₂ :
  ∫ (x : Ω), (∑ k ∈ Finset.range n, (1 - upcrossingStrat a b f N k) * (f (k + 1) - f k)) x ∂μ =
    ∫ (x : Ω), (∑ k ∈ Finset.range n, (f (k + 1) - f k)) x ∂μ -
      ∫ (x : Ω), (∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)) x ∂μ
⊢ ∫ (x : Ω), (∑ k ∈ Finset.range n, (f (k + 1) - f k)) x ∂μ ≤ ∫ (x : Ω), f n x ∂μ - ∫ (x : Ω), f 0 x ∂μ
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: case zero.hi
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
ω : Ω
M : ℕ
hNM : N ≤ M
h : hittingBtwn f (Set.Iic a) (upperCrossingTime a b f N 0 ω) N ω < N
h' : upperCrossingTime a b f N 0 ω < N
⊢ N ≤ N

Tactic:
exact le_rfl

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

Goal state before:
pp: case hi
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
ω : Ω
M : ℕ
hNM : N ≤ M
k : ℕ
ih :
  upperCrossingTime a b f M k ω = upperCrossingTime a b f N k ω ∧
    lowerCrossingTime a b f M k ω = lowerCrossingTime a b f N k ω
h : lowerCrossingTime a b f N (k + 1) ω < N
h' : hittingBtwn f (Set.Ici b) (lowerCrossingTime a b f N k ω) N ω < N
⊢ N ≤ N

Tactic:
exact le_rfl

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

Goal state before:
pp: case hi
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
ω : Ω
M : ℕ
hNM : N ≤ M
h : hittingBtwn f (Set.Ici b) (lowerCrossingTime a b f N n ω) N ω < N
this : lowerCrossingTime a b f M n ω = lowerCrossingTime a b f N n ω
⊢ N ≤ N

Tactic:
exact le_rfl

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

Goal state before:
pp: Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝ : Preorder ι
f : Filtration ι m
i : ι
s : Set Ω
⊢ MeasurableSet s ↔ MeasurableSet s

Tactic:
rw [IsStoppingTime.measurableSet]

Goal state after:
Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝ : Preorder ι
f : Filtration ι m
i : ι
s : Set Ω
⊢ (MeasurableSet s ∧ ∀ (i_1 : ι), MeasurableSet (s ∩ {ω | ↑i ≤ ↑i_1})) ↔ MeasurableSet s
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: case hfi
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
f : ℕ → Ω → ℝ
ℱ : Filtration ℕ m0
inst✝ : IsFiniteMeasure μ
a b : ℝ
hf : Submartingale f ℱ μ
hab : a < b
N : ℕ
⊢ Integrable (fun ω ↦ (f N ω - a)⁺) μ

pp: case f_nn
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
f : ℕ → Ω → ℝ
ℱ : Filtration ℕ m0
inst✝ : IsFiniteMeasure μ
a b : ℝ
hf : Submartingale f ℱ μ
hab : a < b
N : ℕ
⊢ 0 ≤ᵐ[μ] fun ω ↦ (f N ω - a)⁺

Tactic:
· exact (hf.sub_martingale (martingale_const _ _ _)).pos.integrable _

Goal state after:
case f_nn
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
f : ℕ → Ω → ℝ
ℱ : Filtration ℕ m0
inst✝ : IsFiniteMeasure μ
a b : ℝ
hf : Submartingale f ℱ μ
hab : a < b
N : ℕ
⊢ 0 ≤ᵐ[μ] fun ω ↦ (f N ω - a)⁺
Module: Mathlib.Probability.Moments.Basic

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

Tactic:
simp [moment]

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

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
⊢ moment X 1 μ = ∫ (x : Ω), X x ∂μ

Tactic:
simp [moment]

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

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
μ : Measure Ω
t : ℝ
inst✝ : IsFiniteMeasure μ
hμ : μ ≠ 0
c : ℝ
⊢ log (μ.real Set.univ * rexp (t * c)) = log (μ.real Set.univ) + t * c

Tactic:
log_mul _ (exp_pos _).ne'

Goal state after:
Ω : Type u_1
m : MeasurableSpace Ω
μ : Measure Ω
t : ℝ
inst✝ : IsFiniteMeasure μ
hμ : μ ≠ 0
c : ℝ
⊢ log (μ.real Set.univ) + log (rexp (t * c)) = log (μ.real Set.univ) + t * c

Ω : Type u_1
m : MeasurableSpace Ω
μ : Measure Ω
t : ℝ
inst✝ : IsFiniteMeasure μ
hμ : μ ≠ 0
c : ℝ
⊢ μ.real Set.univ ≠ 0
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: Ω : Type u_1
ι : Type u_3
inst✝³ : Nonempty ι
τ : Ω → WithTop ι
E : Type u_4
u : ι → Ω → E
inst✝² : Preorder ι
inst✝¹ : LocallyFiniteOrderBot ι
inst✝ : AddCommMonoid E
N : ι
hbdd : ∀ (ω : Ω), τ ω ≤ ↑N
⊢ stoppedValue u τ = ∑ i ≤ N, {ω | τ ω = ↑i}.indicator (u i)

Tactic:
by
  refine stoppedValue_eq_of_mem_finset fun ω ↦ ?_
  simp only [Finset.coe_Iic, Set.mem_image]
  specialize hbdd ω
  have h_top : τ ω ≠ ⊤ := fun h_contra ↦ by simp [h_contra] at hbdd
  lift τ ω to ι using h_top with i hi
  exact ⟨i, mod_cast hbdd, rfl⟩

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

Goal state before:
pp: 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 : ∀ x ∈ Set.range fun n ↦ f n ω✝, c ≤ x
ω : ℝ
hω : ∃ y, f y ω✝ = -ω
⊢ -ω ∈ Set.range fun n ↦ f n ω✝

Tactic:
simpa only [Set.mem_range]

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

Goal state before:
pp: case e_s
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t : ℝ
inst✝ : IsFiniteMeasure μ
ε : ℝ
ht : 0 ≤ t
h_int : Integrable (fun ω ↦ rexp (t * X ω)) μ
ht_pos : 0 < t
ω : Ω
⊢ ε ≤ X ω ↔ t * ε ≤ t * X ω

Tactic:
exact ⟨fun h => mul_le_mul_of_nonneg_left h ht_pos.le,
        fun h => le_of_mul_le_mul_left h ht_pos⟩

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
hfmono : ∀ᵐ (ω : Ω) ∂μ, ∀ (n : ℕ), f n ω ≤ f (n + 1) ω
hf : StronglyAdapted ℱ f
hint : ∀ (n : ℕ), Integrable (f n) μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (n : ℕ), ‖f (n + 1) ω - f n ω‖ ≤ ↑R
h₀ : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), ‖martingalePart f ℱ μ (i + 1) ω - martingalePart f ℱ μ i ω‖ ≤ 2 * ↑R
⊢ ∀ᵐ (ω : Ω) ∂μ, Tendsto (fun n ↦ f n ω) atTop atTop ↔ Tendsto (fun n ↦ predictablePart f ℱ μ n ω) atTop atTop

Tactic:
simp only [Real.norm_eq_abs, ← NNReal.coe_ofNat, ← NNReal.coe_mul 2 R] at h₀

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
hfmono : ∀ᵐ (ω : Ω) ∂μ, ∀ (n : ℕ), f n ω ≤ f (n + 1) ω
hf : StronglyAdapted ℱ f
hint : ∀ (n : ℕ), Integrable (f n) μ
hbdd : ∀ᵐ (ω : Ω) ∂μ, ∀ (n : ℕ), ‖f (n + 1) ω - f n ω‖ ≤ ↑R
h₀ : ∀ᵐ (ω : Ω) ∂μ, ∀ (i : ℕ), |martingalePart f ℱ μ (i + 1) ω - martingalePart f ℱ μ i ω| ≤ ↑(2 * R)
⊢ ∀ᵐ (ω : Ω) ∂μ, Tendsto (fun n ↦ f n ω) atTop atTop ↔ Tendsto (fun n ↦ predictablePart f ℱ μ n ω) atTop atTop
Module: Mathlib.Probability.Moments.Basic

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t : ℝ
inst✝ : IsFiniteMeasure μ
ε : ℝ
ht : 0 ≤ t
h_int : Integrable (fun ω ↦ rexp (t * X ω)) μ
ht_pos : 0 < t
⊢ (rexp (t * ε))⁻¹ * ∫ (x : Ω), (fun ω ↦ rexp (t * X ω)) x ∂μ = rexp (-(t * ε)) * mgf X μ t

Tactic:
exp_neg

Goal state after:
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t : ℝ
inst✝ : IsFiniteMeasure μ
ε : ℝ
ht : 0 ≤ t
h_int : Integrable (fun ω ↦ rexp (t * X ω)) μ
ht_pos : 0 < t
⊢ (rexp (t * ε))⁻¹ * ∫ (x : Ω), (fun ω ↦ rexp (t * X ω)) x ∂μ = (rexp (t * ε))⁻¹ * mgf X μ t
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|
p : ℝ
hp : 0 ≤ p
ht : t ≠ 0
hX : AEMeasurable X μ
a : Ω
⊢ |X a| ^ p * (rexp (v * X a) * rexp (x * |X a|)) ≤ (p / (|t| - x)) ^ p * (rexp (v * X a) * rexp (|t| * |X a|))

Tactic:
mul_comm (exp (v * X a)),

Goal state after:
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
⊢ |X a| ^ p * (rexp (x * |X a|) * rexp (v * X a)) ≤ (p / (|t| - x)) ^ p * (rexp (|t| * |X a|) * rexp (v * X a))
Module: Mathlib.Probability.Moments.MGFAnalytic

Goal state before:
pp: case hc
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
v : ℝ
h : v ∈ interior (integrableExpSet X μ)
hμ : ¬μ = 0
h_mem : ∀ᶠ (y : ℝ) in 𝓝 v, y ∈ interior (integrableExpSet X μ)
h_d_cgf : deriv (cgf X μ) =ᶠ[𝓝 v] fun u ↦ (∫ (x : Ω), (fun ω ↦ X ω * rexp (u * X ω)) x ∂μ) / mgf X μ u
h_d_mgf : deriv (mgf X μ) =ᶠ[𝓝 v] fun u ↦ ∫ (x : Ω), (fun ω ↦ X ω * rexp (u * X ω)) x ∂μ
⊢ DifferentiableAt ℝ (fun u ↦ ∫ (ω : Ω), X ω * rexp (u * X ω) ∂μ) v

Tactic:
rw [h_d_mgf.symm.differentiableAt_iff, ← iteratedDeriv_one]

Goal state after:
case hc
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
v : ℝ
h : v ∈ interior (integrableExpSet X μ)
hμ : ¬μ = 0
h_mem : ∀ᶠ (y : ℝ) in 𝓝 v, y ∈ interior (integrableExpSet X μ)
h_d_cgf : deriv (cgf X μ) =ᶠ[𝓝 v] fun u ↦ (∫ (x : Ω), (fun ω ↦ X ω * rexp (u * X ω)) x ∂μ) / mgf X μ u
h_d_mgf : deriv (mgf X μ) =ᶠ[𝓝 v] fun u ↦ ∫ (x : Ω), (fun ω ↦ X ω * rexp (u * X ω)) x ∂μ
⊢ DifferentiableAt ℝ (iteratedDeriv 1 (mgf X μ)) v
Module: Mathlib.Probability.Moments.ComplexMGF

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
Ω' : Type u_3
mΩ' : MeasurableSpace Ω'
Y : Ω' → ℝ
μ' : Measure Ω'
hXY : mgf X μ = mgf Y μ'
hμμ' : μ = 0 ↔ μ' = 0
⊢ Set.EqOn (complexMGF X μ) (complexMGF Y μ') {z | z.re ∈ interior (integrableExpSet X μ)}

Tactic:
by_cases h_empty : interior (integrableExpSet X μ) = ∅

Goal state after:
case pos
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
Ω' : Type u_3
mΩ' : MeasurableSpace Ω'
Y : Ω' → ℝ
μ' : Measure Ω'
hXY : mgf X μ = mgf Y μ'
hμμ' : μ = 0 ↔ μ' = 0
h_empty : interior (integrableExpSet X μ) = ∅
⊢ Set.EqOn (complexMGF X μ) (complexMGF Y μ') {z | z.re ∈ interior (integrableExpSet X μ)}

case neg
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
Ω' : Type u_3
mΩ' : MeasurableSpace Ω'
Y : Ω' → ℝ
μ' : Measure Ω'
hXY : mgf X μ = mgf Y μ'
hμμ' : μ = 0 ↔ μ' = 0
h_empty : ¬interior (integrableExpSet X μ) = ∅
⊢ Set.EqOn (complexMGF X μ) (complexMGF Y μ') {z | z.re ∈ interior (integrableExpSet X μ)}
Module: Mathlib.Probability.Distributions.Gaussian.Real

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
p : Measure Ω
μ : ℝ
v : ℝ≥0
X : Ω → ℝ
hX : Measure.map X p = gaussianReal μ v
z : ℂ
hX_meas : AEMeasurable X p
⊢ complexMGF X p z = cexp (z * ↑μ + ↑↑v * z ^ 2 / 2)

Tactic:
rw [← complexMGF_id_map hX_meas, hX, complexMGF_id_gaussianReal]

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

Goal state before:
pp: E : Type u_1
inst✝⁴ : NormedAddCommGroup E
inst✝³ : NormedSpace ℝ E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : IsGaussian μ
L : StrongDual ℝ E
⊢ charFun (Measure.map (⇑L) μ) 1 = charFun (gaussianReal (∫ (x : E), L x ∂μ) Var[⇑L; μ].toNNReal) 1

Tactic:
by
    rw [IsGaussian.map_eq_gaussianReal L]

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

Goal state before:
pp: case e_a.e_a
E : Type u_1
inst✝⁴ : NormedAddCommGroup E
inst✝³ : NormedSpace ℝ E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : IsGaussian μ
L : StrongDual ℝ E
⊢ ↑(∫ (x : E), L x ∂μ) = ∫ (x : E), ↑(L x) ∂μ

Tactic:
integral_complex_ofReal

Goal state after:
case e_a.e_a
E : Type u_1
inst✝⁴ : NormedAddCommGroup E
inst✝³ : NormedSpace ℝ E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : IsGaussian μ
L : StrongDual ℝ E
⊢ ↑(∫ (x : E), L x ∂μ) = ↑(∫ (x : E), L x ∂μ)
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: case e_a.e_a
E : Type u_1
inst✝⁴ : NormedAddCommGroup E
inst✝³ : NormedSpace ℝ E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : IsFiniteMeasure μ
h : ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp ((∫ (x : E), ↑(L x) ∂μ) * I - ↑Var[⇑L; μ] / 2)
L : StrongDual ℝ E
u : ℝ
⊢ ↑u * ∫ (a : E), ↑(L a) ∂μ = ↑u * ↑(∫ (x : E), L x ∂μ)

Tactic:
integral_complex_ofReal

Goal state after:
case e_a.e_a
E : Type u_1
inst✝⁴ : NormedAddCommGroup E
inst✝³ : NormedSpace ℝ E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : IsFiniteMeasure μ
h : ∀ (L : StrongDual ℝ E), charFunDual μ L = cexp ((∫ (x : E), ↑(L x) ∂μ) * I - ↑Var[⇑L; μ] / 2)
L : StrongDual ℝ E
u : ℝ
⊢ ↑u * ↑(∫ (x : E), L x ∂μ) = ↑u * ↑(∫ (x : E), L x ∂μ)
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
L : StrongDual ℝ E
hL_comp : (⇑L ∘ fun x ↦ x + c) = fun x ↦ L x + L c
⊢ cexp (↑(∫ (x : E), L x ∂μ) * I - ↑Var[⇑L; μ] / 2 + ↑(L c) * I) =
    cexp ((∫ (x : E), ↑(L (x + c)) ∂μ) * I - ↑Var[⇑L; μ] / 2)

Tactic:
integral_complex_ofReal

Goal state after:
E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
L : StrongDual ℝ E
hL_comp : (⇑L ∘ fun x ↦ x + c) = fun x ↦ L x + L c
⊢ cexp (↑(∫ (x : E), L x ∂μ) * I - ↑Var[⇑L; μ] / 2 + ↑(L c) * I) =
    cexp (↑(∫ (x : E), L (x + c) ∂μ) * I - ↑Var[⇑L; μ] / 2)
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
⊢ μ {x | ‖x‖ ≤ a} * μ {x | b < ‖x‖} = (μ.prod μ) ({x | ‖x‖ ≤ a} ×ˢ {y | b < ‖y‖})

Tactic:
Measure.prod_prod

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 {x | ‖x‖ ≤ a} * μ {x | b < ‖x‖} = μ {x | ‖x‖ ≤ a} * μ {y | b < ‖y‖}
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: case e_a.e_a
E : Type u_1
F : Type u_2
inst✝¹⁰ : NormedAddCommGroup E
inst✝⁹ : NormedSpace ℝ E
inst✝⁸ : MeasurableSpace E
inst✝⁷ : BorelSpace E
inst✝⁶ : NormedAddCommGroup F
inst✝⁵ : NormedSpace ℝ F
inst✝⁴ : MeasurableSpace F
inst✝³ : BorelSpace F
μ : Measure E
inst✝² : IsGaussian μ
inst✝¹ : SecondCountableTopologyEither E F
ν : Measure F
inst✝ : IsGaussian ν
L : StrongDual ℝ (E × F)
L₁ : E →L[ℝ] ℝ := L ∘SL ContinuousLinearMap.inl ℝ E F
hL₁ : L₁ = L ∘SL ContinuousLinearMap.inl ℝ E F
L₂ : F →L[ℝ] ℝ := L ∘SL ContinuousLinearMap.inr ℝ E F
hL₂ : L₂ = L ∘SL ContinuousLinearMap.inr ℝ E F
⊢ ∫ (x : E), ↑(L₁ x) ∂μ + ∫ (x : F), ↑(L₂ x) ∂ν = ∫ (x : E × F), ↑(L x) ∂μ.prod ν

Tactic:
integral_complex_ofReal

Goal state after:
case e_a.e_a
E : Type u_1
F : Type u_2
inst✝¹⁰ : NormedAddCommGroup E
inst✝⁹ : NormedSpace ℝ E
inst✝⁸ : MeasurableSpace E
inst✝⁷ : BorelSpace E
inst✝⁶ : NormedAddCommGroup F
inst✝⁵ : NormedSpace ℝ F
inst✝⁴ : MeasurableSpace F
inst✝³ : BorelSpace F
μ : Measure E
inst✝² : IsGaussian μ
inst✝¹ : SecondCountableTopologyEither E F
ν : Measure F
inst✝ : IsGaussian ν
L : StrongDual ℝ (E × F)
L₁ : E →L[ℝ] ℝ := L ∘SL ContinuousLinearMap.inl ℝ E F
hL₁ : L₁ = L ∘SL ContinuousLinearMap.inl ℝ E F
L₂ : F →L[ℝ] ℝ := L ∘SL ContinuousLinearMap.inr ℝ E F
hL₂ : L₂ = L ∘SL ContinuousLinearMap.inr ℝ E F
⊢ ↑(∫ (x : E), L₁ x ∂μ) + ↑(∫ (x : F), L₂ x ∂ν) = ↑(∫ (x : E × F), L x ∂μ.prod ν)
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁶ : NormedAddCommGroup E
inst✝⁵ : NormedSpace ℝ E
inst✝⁴ : MeasurableSpace E
inst✝³ : BorelSpace E
μ : Measure E
inst✝² : IsGaussian μ
inst✝¹ : SecondCountableTopology E
inst✝ : CompleteSpace E
hμ : ∀ (L : StrongDual ℝ E), ∫ (x : E), L x ∂μ = 0
θ : ℝ
L : StrongDual ℝ (E × E)
x : E
⊢ ((L ∘SL ContinuousLinearMap.rotation θ) ∘SL ContinuousLinearMap.inl ℝ E E) x =
    (Real.cos θ • L ∘SL ContinuousLinearMap.inl ℝ E E - Real.sin θ • L ∘SL ContinuousLinearMap.inr ℝ E E) x

Tactic:
simp only [ContinuousLinearMap.comp_apply, ContinuousLinearMap.inl_apply,
      ContinuousLinearMap.rotation_apply, smul_zero, add_zero]

Goal state after:
E : Type u_1
inst✝⁶ : NormedAddCommGroup E
inst✝⁵ : NormedSpace ℝ E
inst✝⁴ : MeasurableSpace E
inst✝³ : BorelSpace E
μ : Measure E
inst✝² : IsGaussian μ
inst✝¹ : SecondCountableTopology E
inst✝ : CompleteSpace E
hμ : ∀ (L : StrongDual ℝ E), ∫ (x : E), L x ∂μ = 0
θ : ℝ
L : StrongDual ℝ (E × E)
x : E
⊢ L (Real.cos θ • x, -Real.sin θ • x) =
    (Real.cos θ • L ∘SL ContinuousLinearMap.inl ℝ E E - Real.sin θ • L ∘SL ContinuousLinearMap.inr ℝ E E) x
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝⁴ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝³ : NormedSpace ℝ E
inst✝² : BorelSpace E
inst✝¹ : CompleteSpace E
inst✝ : IsFiniteMeasure μ
h : MemLp id 2 μ
L₁ L₂ : StrongDual ℝ E
⊢ ∫ (x : E), (L₁ x - ∫ (x : E), L₁ x ∂μ) * (L₂ x - ∫ (x : E), L₂ x ∂μ) ∂μ =
    ∫ (x : E), L₁ (x - ∫ (x : E), id x ∂μ) * L₂ (x - ∫ (x : E), id x ∂μ) ∂μ

Tactic:
have hL (L : StrongDual ℝ E) : μ[L] = L (∫ x, x ∂μ) :=
    L.integral_comp_comm (h.integrable (by simp))

Goal state after:
E : Type u_1
inst✝⁴ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝³ : NormedSpace ℝ E
inst✝² : BorelSpace E
inst✝¹ : CompleteSpace E
inst✝ : IsFiniteMeasure μ
h : MemLp id 2 μ
L₁ L₂ : StrongDual ℝ E
hL : ∀ (L : StrongDual ℝ E), ∫ (x : E), L x ∂μ = L (∫ (x : E), x ∂μ)
⊢ ∫ (x : E), (L₁ x - ∫ (x : E), L₁ x ∂μ) * (L₂ x - ∫ (x : E), L₂ x ∂μ) ∂μ =
    ∫ (x : E), L₁ (x - ∫ (x : E), id x ∂μ) * L₂ (x - ∫ (x : E), id x ∂μ) ∂μ
Module: Mathlib.Probability.Distributions.Gaussian.Multivariate

Goal state before:
pp: E : Type u_2
inst✝⁴ : NormedAddCommGroup E
inst✝³ : InnerProductSpace ℝ E
inst✝² : FiniteDimensional ℝ E
inst✝¹ : MeasurableSpace E
inst✝ : BorelSpace E
t : E
⊢ ∏ x, ∫ (x_1 : ℝ), cexp (↑(⟪(stdOrthonormalBasis ℝ E) x, t⟫ * x_1) * I) ∂gaussianReal 0 1 = cexp (-↑‖t‖ ^ 2 / 2)

Tactic:
ofReal_mul,

Goal state after:
E : Type u_2
inst✝⁴ : NormedAddCommGroup E
inst✝³ : InnerProductSpace ℝ E
inst✝² : FiniteDimensional ℝ E
inst✝¹ : MeasurableSpace E
inst✝ : BorelSpace E
t : E
⊢ ∏ x, ∫ (x_1 : ℝ), cexp (↑⟪(stdOrthonormalBasis ℝ E) x, t⟫ * ↑x_1 * I) ∂gaussianReal 0 1 = cexp (-↑‖t‖ ^ 2 / 2)
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁶ : NormedAddCommGroup E
inst✝⁵ : NormedSpace ℝ E
inst✝⁴ : MeasurableSpace E
inst✝³ : BorelSpace E
inst✝² : SecondCountableTopology E
inst✝¹ : CompleteSpace E
μ : Measure E
inst✝ : IsGaussian μ
⊢ ∃ C, 0 < C ∧ Integrable (fun x ↦ rexp (C * ‖x‖ ^ 2)) μ

Tactic:
obtain ⟨C, hC_pos, hC⟩ : ∃ C, 0 < C
      ∧ Integrable (fun x ↦ rexp (C * ‖x‖ ^ 2)) (μ ∗ μ.map (ContinuousLinearEquiv.neg ℝ)) :=
    exists_integrable_exp_sq_of_map_rotation_eq_self
      (map_rotation_eq_self_of_forall_strongDual_eq_zero
        (integral_dual_conv_map_neg_eq_zero (μ := μ)) _)

Goal state after:
E : Type u_1
inst✝⁶ : NormedAddCommGroup E
inst✝⁵ : NormedSpace ℝ E
inst✝⁴ : MeasurableSpace E
inst✝³ : BorelSpace E
inst✝² : SecondCountableTopology E
inst✝¹ : CompleteSpace E
μ : Measure E
inst✝ : IsGaussian μ
C : ℝ
hC_pos : 0 < C
hC : Integrable (fun x ↦ rexp (C * ‖x‖ ^ 2)) (μ ∗ Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)
⊢ ∃ C, 0 < C ∧ Integrable (fun x ↦ rexp (C * ‖x‖ ^ 2)) μ
Module: Mathlib.Probability.Distributions.Gaussian.Multivariate

Goal state before:
pp: ι : Type u_1
inst✝¹ : Fintype ι
inst✝ : DecidableEq ι
μ : EuclideanSpace ℝ ι
S : Matrix ι ι ℝ
hS : S.PosSemidef
x y : EuclideanSpace ℝ ι
h : (fun x ↦ μ + x) ∘ ⇑(toEuclideanCLM (CFC.sqrt S)) = fun x ↦ μ + (toEuclideanCLM (CFC.sqrt S)) x
⊢ ((covarianceBilin (Measure.map (fun x ↦ μ + (toEuclideanCLM (CFC.sqrt S)) x) (stdGaussian (EuclideanSpace ℝ ι)))) x)
      y =
    x.ofLp ⬝ᵥ S *ᵥ y.ofLp

Tactic:
rw [← h, ← Measure.map_map (measurable_const_add μ) (by fun_prop), covarianceBilin_map_const_add,
    covarianceBilin_map, covarianceBilin_stdGaussian, innerSL_apply_apply,
    ContinuousLinearMap.adjoint_inner_left, IsSelfAdjoint.adjoint_eq,
    ← ContinuousLinearMap.comp_apply, ← ContinuousLinearMap.mul_def, ← map_mul,
      CFC.sqrt_mul_sqrt_self _ hS.nonneg, inner_toEuclideanCLM]

Goal state after:
ι : Type u_1
inst✝¹ : Fintype ι
inst✝ : DecidableEq ι
μ : EuclideanSpace ℝ ι
S : Matrix ι ι ℝ
hS : S.PosSemidef
x y : EuclideanSpace ℝ ι
h : (fun x ↦ μ + x) ∘ ⇑(toEuclideanCLM (CFC.sqrt S)) = fun x ↦ μ + (toEuclideanCLM (CFC.sqrt S)) x
⊢ IsSelfAdjoint (toEuclideanCLM (CFC.sqrt S))

case h
ι : Type u_1
inst✝¹ : Fintype ι
inst✝ : DecidableEq ι
μ : EuclideanSpace ℝ ι
S : Matrix ι ι ℝ
hS : S.PosSemidef
x y : EuclideanSpace ℝ ι
h : (fun x ↦ μ + x) ∘ ⇑(toEuclideanCLM (CFC.sqrt S)) = fun x ↦ μ + (toEuclideanCLM (CFC.sqrt S)) x
⊢ MemLp id 2 (stdGaussian (EuclideanSpace ℝ ι))
Module: Mathlib.Probability.Independence.CharacteristicFunction

Goal state before:
pp: E : Type u_2
mE : MeasurableSpace E
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : BorelSpace E
inst✝³ : SecondCountableTopology E
inst✝² : InnerProductSpace ℝ E
μ ν : Measure E
inst✝¹ : IsProbabilityMeasure μ
inst✝ : IsProbabilityMeasure ν
⊢ charFun (Measure.map (fun p ↦ p.1 + p.2) (μ.prod ν)) = charFun μ * charFun ν

Tactic:
rw [IndepFun.charFun_map_fun_add_eq_mul, measurePreserving_fst.map_eq,
    measurePreserving_snd.map_eq]
  any_goals fun_prop
  exact indepFun_prod (X := id) (Y := id) measurable_id measurable_id

Goal state after: