mathlib-initiative/mathlib-tactics huggingface dataset:
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 ≤
    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

Tactic:
rw [upperCrossingTime_eq_of_upcrossingsBefore_lt hab (Nat.lt_succ_self _)]

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 (↑N).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✝⁵ : Add ι
inst✝⁴ : LinearOrder ι
inst✝³ : CanonicallyOrderedAdd ι
inst✝² : Countable ι
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
f : Filtration ι m
τ : Ω → WithTop ι
hτ : IsStoppingTime f τ
i j : ι
⊢ MeasurableSet {ω | (fun ω ↦ τ ω + ↑i) ω ≤ ↑j}

Tactic:
have h : {ω | τ ω + i ≤ j} = ⋃ k : {k | k + i ≤ j}, {ω | τ ω = k} := by
    ext ω
    simp only [Set.mem_ofPred_eq, Set.mem_iUnion]
    cases τ ω with
    | top => simp
    | coe a => simp; norm_cast

Goal state after:
Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝⁵ : Add ι
inst✝⁴ : LinearOrder ι
inst✝³ : CanonicallyOrderedAdd ι
inst✝² : Countable ι
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
f : Filtration ι m
τ : Ω → WithTop ι
hτ : IsStoppingTime f τ
i j : ι
h : {ω | τ ω + ↑i ≤ ↑j} = ⋃ k, {ω | τ ω = ↑↑k}
⊢ MeasurableSet {ω | (fun ω ↦ τ ω + ↑i) ω ≤ ↑j}
Module: Mathlib.Probability.Martingale.Convergence

Goal state before:
pp: case refine_1
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
ℱ : Filtration ℕ m0
a b : ℝ
f : ℕ → Ω → ℝ
R : ℝ≥0
inst✝ : IsFiniteMeasure μ
hf : Submartingale f ℱ μ
hbdd : ∀ (n : ℕ), eLpNorm (f n) 1 μ ≤ ↑R
hab : a < b
this : ∫⁻ (ω : Ω), upcrossings a b f ω ∂μ ≤ (⨆ N, ∫⁻ (ω : Ω), ENNReal.ofReal (f N ω - a)⁺ ∂μ) / ENNReal.ofReal (b - a)
hR' : ∀ (n : ℕ), ∫⁻ (ω : Ω), ↑‖f n ω - a‖₊ ∂μ ≤ ↑R + ↑‖a‖₊ * μ Set.univ
n : ℕ
ω : Ω
⊢ (f n ω - a)⁺ ≤ ‖f n ω - a‖

Tactic:
by_cases! hnonneg : 0 ≤ f n ω - a

Goal state after:
case pos
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
ℱ : Filtration ℕ m0
a b : ℝ
f : ℕ → Ω → ℝ
R : ℝ≥0
inst✝ : IsFiniteMeasure μ
hf : Submartingale f ℱ μ
hbdd : ∀ (n : ℕ), eLpNorm (f n) 1 μ ≤ ↑R
hab : a < b
this : ∫⁻ (ω : Ω), upcrossings a b f ω ∂μ ≤ (⨆ N, ∫⁻ (ω : Ω), ENNReal.ofReal (f N ω - a)⁺ ∂μ) / ENNReal.ofReal (b - a)
hR' : ∀ (n : ℕ), ∫⁻ (ω : Ω), ↑‖f n ω - a‖₊ ∂μ ≤ ↑R + ↑‖a‖₊ * μ Set.univ
n : ℕ
ω : Ω
hnonneg : 0 ≤ f n ω - a
⊢ (f n ω - a)⁺ ≤ ‖f n ω - a‖

case neg
Ω : Type u_1
m0 : MeasurableSpace Ω
μ : Measure Ω
ℱ : Filtration ℕ m0
a b : ℝ
f : ℕ → Ω → ℝ
R : ℝ≥0
inst✝ : IsFiniteMeasure μ
hf : Submartingale f ℱ μ
hbdd : ∀ (n : ℕ), eLpNorm (f n) 1 μ ≤ ↑R
hab : a < b
this : ∫⁻ (ω : Ω), upcrossings a b f ω ∂μ ≤ (⨆ N, ∫⁻ (ω : Ω), ENNReal.ofReal (f N ω - a)⁺ ∂μ) / ENNReal.ofReal (b - a)
hR' : ∀ (n : ℕ), ∫⁻ (ω : Ω), ↑‖f n ω - a‖₊ ∂μ ≤ ↑R + ↑‖a‖₊ * μ Set.univ
n : ℕ
ω : Ω
hnonneg : f n ω - a < 0
⊢ (f n ω - a)⁺ ≤ ‖f n ω - a‖
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: 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
N : ℕ
hab : b - a ≤ 0
⊢ 0 ≤ ∫ (x : Ω), ↑(upcrossingsBefore a b f N x) ∂μ

Tactic:
by positivity

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

Goal state before:
pp: Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝ : LinearOrder ι
f : Filtration ι m
τ : Ω → WithTop ι
hτ : IsStoppingTime f τ
s : Set Ω
i : ι
⊢ MeasurableSet s ↔ MeasurableSet s ∧ MeasurableSet s

Tactic:
by
  rw [measurableSpace_min_const hτ]; apply MeasurableSpace.measurableSet_inf

Goal state after:
Module: Mathlib.Probability.BorelCantelli

Goal state before:
pp: 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
⊢ 0 ≤ (∑ k ∈ Finset.range n, μ (s (k + 1))).toReal

Tactic:
by positivity

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 a b : ℝ
ha : Integrable (fun ω ↦ rexp (a * X ω)) μ
hb : Integrable (fun ω ↦ rexp (b * X ω)) μ
hat : a ≤ t
htb : t ≤ b
ω : Ω
⊢ 0 ≤ rexp (a * X ω) + rexp (b * X ω)

Tactic:
by positivity

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

Goal state before:
pp: Ω : Type u_2
m0 : MeasurableSpace Ω
ℱ : Filtration ℕ m0
μ : Measure Ω
s : ℕ → Set Ω
n : ℕ
this :
  martingalePart (process s) ℱ μ n = ∑ k ∈ Finset.range n, ((s (k + 1)).indicator 1 - μ[(s (k + 1)).indicator 1 | ↑ℱ k])
⊢ predictablePart (process s) ℱ μ n = ∑ k ∈ Finset.range n, μ[(s (k + 1)).indicator 1 | ↑ℱ k]

Tactic:
simp_rw [martingalePart, process, Finset.sum_sub_distrib] at this

Goal state after:
Ω : Type u_2
m0 : MeasurableSpace Ω
ℱ : Filtration ℕ m0
μ : Measure Ω
s : ℕ → Set Ω
n : ℕ
this :
  ∑ k ∈ Finset.range n, (s (k + 1)).indicator 1 - predictablePart (process s) ℱ μ n =
    ∑ k ∈ Finset.range n, (s (k + 1)).indicator 1 - ∑ x ∈ Finset.range n, μ[(s (x + 1)).indicator 1 | ↑ℱ x]
⊢ predictablePart (process s) ℱ μ n = ∑ k ∈ Finset.range n, μ[(s (k + 1)).indicator 1 | ↑ℱ k]
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: Ω✝ : Type u_1
m✝ : MeasurableSpace Ω✝
X✝ : Ω✝ → ℝ
μ✝ : Measure Ω✝
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t₁ : ℝ
ht₁ : t₁ ∈ integrableExpSet X μ
t₂ : ℝ
ht₂ : t₂ ∈ integrableExpSet X μ
a b : ℝ
ha : 0 ≤ a
hb : 0 ≤ b
hab : a + b = 1
h_le : t₁ ≤ t₂
⊢ t₁ = a * t₁ + b * t₁

Tactic:
← add_mul,

Goal state after:
Ω✝ : Type u_1
m✝ : MeasurableSpace Ω✝
X✝ : Ω✝ → ℝ
μ✝ : Measure Ω✝
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t₁ : ℝ
ht₁ : t₁ ∈ integrableExpSet X μ
t₂ : ℝ
ht₂ : t₂ ∈ integrableExpSet X μ
a b : ℝ
ha : 0 ≤ a
hb : 0 ≤ b
hab : a + b = 1
h_le : t₁ ≤ t₂
⊢ t₁ = (a + b) * t₁
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: Ω✝ : Type u_1
m✝ : MeasurableSpace Ω✝
X✝ : Ω✝ → ℝ
μ✝ : Measure Ω✝
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t₁ : ℝ
ht₁ : t₁ ∈ integrableExpSet X μ
t₂ : ℝ
ht₂ : t₂ ∈ integrableExpSet X μ
a b : ℝ
ha : 0 ≤ a
hb : 0 ≤ b
hab : a + b = 1
h_le : t₁ ≤ t₂
⊢ a * t₂ + b * t₂ = t₂

Tactic:
← add_mul,

Goal state after:
Ω✝ : Type u_1
m✝ : MeasurableSpace Ω✝
X✝ : Ω✝ → ℝ
μ✝ : Measure Ω✝
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t₁ : ℝ
ht₁ : t₁ ∈ integrableExpSet X μ
t₂ : ℝ
ht₂ : t₂ ∈ integrableExpSet X μ
a b : ℝ
ha : 0 ≤ a
hb : 0 ≤ b
hab : a + b = 1
h_le : t₁ ≤ t₂
⊢ (a + b) * t₂ = t₂
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_int_pos : Integrable (fun ω ↦ rexp ((v + t) * X ω)) μ
ht_int_neg : Integrable (fun ω ↦ rexp ((v - t) * X ω)) μ
h_int_add : Integrable (fun a ↦ rexp ((v + t) * X a) + rexp ((v - t) * X a)) μ
ω : Ω
⊢ 0 ≤ rexp ((v + t) * X ω) + rexp ((v - t) * X ω)

Tactic:
by positivity

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

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : Ω → ℝ
t b : ℝ
ht : 0 ≤ t
hX : AEMeasurable X μ
hb✝ : ∀ᵐ (ω : Ω) ∂μ, X ω ≤ b
ω : Ω
hb : X ω ≤ b
⊢ 0 ≤ rexp (t * X ω)

Tactic:
by positivity

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

Goal state before:
pp: case refine_2.inl
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
h_int_add : Integrable (fun a ↦ rexp ((v + t) * X a) + rexp ((v - t) * X a)) μ
ω : Ω
h_nonneg : 0 ≤ X ω
⊢ rexp (t * X ω + v * X ω) ≤ rexp ((v + t) * X ω) + rexp ((v - t) * X ω)

Tactic:
← add_mul,

Goal state after:
case refine_2.inl
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
h_int_add : Integrable (fun a ↦ rexp ((v + t) * X a) + rexp ((v - t) * X a)) μ
ω : Ω
h_nonneg : 0 ≤ X ω
⊢ rexp ((t + v) * X ω) ≤ rexp ((v + t) * X ω) + rexp ((v - t) * X ω)
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: case refine_2.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
h_int_add : Integrable (fun a ↦ rexp ((v + t) * X a) + rexp ((v - t) * X a)) μ
ω : Ω
h_nonpos : X ω ≤ 0
⊢ rexp (-t * X ω + v * X ω) ≤ rexp ((v + t) * X ω) + rexp ((v - t) * X ω)

Tactic:
← add_mul,

Goal state after:
case refine_2.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
h_int_add : Integrable (fun a ↦ rexp ((v + t) * X a) + rexp ((v - t) * X a)) μ
ω : Ω
h_nonpos : X ω ≤ 0
⊢ rexp ((-t + v) * X ω) ≤ rexp ((v + t) * X ω) + rexp ((v - t) * X ω)
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: Ω : Type u_1
β : Type u_2
u : ℕ → Ω → β
τ π : Ω → ℕ∞
inst✝ : AddCommGroup β
hle : τ ≤ π
hπ : ∀ (ω : Ω), ↑(π ω) ≠ ∞
⊢ stoppedValue u π - stoppedValue u τ = fun ω ↦ (∑ i ∈ Finset.Ico (untopA (τ ω)) (untopA (π ω)), (u (i + 1) - u i)) ω

Tactic:
by
  ext ω
  have h_le' : (τ ω).untopA ≤ (π ω).untopA := untopA_mono (mod_cast hπ ω) (hle ω)
  rw [Finset.sum_Ico_eq_sub _ h_le', Finset.sum_range_sub, Finset.sum_range_sub]
  simp [stoppedValue]

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

Goal state before:
pp: x t p : ℝ
hp : 0 ≤ p
ht : 0 < t
hp_zero : ¬p = 0
h_x_le : ∀ (c : ℝ), 0 < c → x ≤ c⁻¹ * rexp (c * x)
h_neg_x_le : ∀ (c : ℝ), 0 < c → -x ≤ c⁻¹ * rexp (-c * x)
h_abs_le : ∀ (c : ℝ), 0 < c → |x| ≤ c⁻¹ * max (rexp (c * x)) (rexp (-c * x))
⊢ 0 ≤ (t / p)⁻¹

Tactic:
by positivity

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

Goal state before:
pp: x t p : ℝ
hp : 0 ≤ p
ht : 0 < t
hp_zero : ¬p = 0
h_x_le : ∀ (c : ℝ), 0 < c → x ≤ c⁻¹ * rexp (c * x)
h_neg_x_le : ∀ (c : ℝ), 0 < c → -x ≤ c⁻¹ * rexp (-c * x)
h_abs_le : ∀ (c : ℝ), 0 < c → |x| ≤ c⁻¹ * max (rexp (c * x)) (rexp (-c * x))
⊢ 0 ≤ max (rexp (t / p * x)) (rexp (-t / p * x))

Tactic:
by positivity

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

Goal state before:
pp: x t p : ℝ
hp : 0 ≤ p
ht : 0 < t
hp_zero : ¬p = 0
h_x_le : ∀ (c : ℝ), 0 < c → x ≤ c⁻¹ * rexp (c * x)
h_neg_x_le : ∀ (c : ℝ), 0 < c → -x ≤ c⁻¹ * rexp (-c * x)
h_abs_le : ∀ (c : ℝ), 0 < c → |x| ≤ c⁻¹ * max (rexp (c * x)) (rexp (-c * x))
⊢ ((t / p)⁻¹ * max (rexp (t / p * x)) (rexp (-t / p * x))) ^ p = (p / t) ^ p * max (rexp (t * x)) (rexp (-t * x))

Tactic:
rw [mul_rpow (by positivity) (by positivity)]

Goal state after:
x t p : ℝ
hp : 0 ≤ p
ht : 0 < t
hp_zero : ¬p = 0
h_x_le : ∀ (c : ℝ), 0 < c → x ≤ c⁻¹ * rexp (c * x)
h_neg_x_le : ∀ (c : ℝ), 0 < c → -x ≤ c⁻¹ * rexp (-c * x)
h_abs_le : ∀ (c : ℝ), 0 < c → |x| ≤ c⁻¹ * max (rexp (c * x)) (rexp (-c * x))
⊢ (t / p)⁻¹ ^ p * max (rexp (t / p * x)) (rexp (-t / p * x)) ^ p = (p / t) ^ p * max (rexp (t * x)) (rexp (-t * x))
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: x t p : ℝ
hp : 0 ≤ p
ht : 0 < t
hp_zero : ¬p = 0
h_x_le : ∀ (c : ℝ), 0 < c → x ≤ c⁻¹ * rexp (c * x)
h_neg_x_le : ∀ (c : ℝ), 0 < c → -x ≤ c⁻¹ * rexp (-c * x)
h_abs_le : ∀ (c : ℝ), 0 < c → |x| ≤ c⁻¹ * max (rexp (c * x)) (rexp (-c * x))
⊢ 0 ≤ rexp (t / p * x)

Tactic:
by positivity

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

Goal state before:
pp: x t p : ℝ
hp : 0 ≤ p
ht : 0 < t
hp_zero : ¬p = 0
h_x_le : ∀ (c : ℝ), 0 < c → x ≤ c⁻¹ * rexp (c * x)
h_neg_x_le : ∀ (c : ℝ), 0 < c → -x ≤ c⁻¹ * rexp (-c * x)
h_abs_le : ∀ (c : ℝ), 0 < c → |x| ≤ c⁻¹ * max (rexp (c * x)) (rexp (-c * x))
⊢ 0 ≤ rexp (-t / p * x)

Tactic:
by positivity

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

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
h : 0 ∈ interior (integrableExpSet X μ)
⊢ deriv (mgf X μ) 0 = ∫ (x : Ω), X x ∂μ

Tactic:
by
  simp [deriv_mgf h]

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

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
v : ℝ
h : v ∈ interior (integrableExpSet X μ)
⊢ AnalyticAt ℝ (cgf X μ) v

Tactic:
by_cases hμ : μ = 0
  · simp only [hμ, cgf_zero_measure]
    exact analyticAt_const
  · exact (analyticAt_mgf h).log <| mgf_pos' hμ (interior_subset (s := integrableExpSet X μ) h)

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
n : ℕ
⊢ 0 ≤ ↑n

Tactic:
by positivity

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 : ℝ
ht : t ≠ 0
ht_int_pos : Integrable (fun ω ↦ rexp (t * X ω)) μ
ht_int_neg : Integrable (fun ω ↦ rexp (-t * X ω)) μ
n : ℕ
⊢ 0 ≤ ↑n

Tactic:
by positivity

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

Goal state before:
pp: l u v : ℝ
hv : v ∈ Set.Ioo l u
h_pos : 0 < min (v - l) (u - v)
⊢ 0 ≤ min (v - l) (u - v) / 2

Tactic:
by positivity

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

Goal state before:
pp: l u v : ℝ
hv : v ∈ Set.Ioo l u
h_pos : 0 < min (v - l) (u - v)
⊢ 0 < min (v - l) (u - v)

Tactic:
by positivity

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
v : ℝ
hv : v ∈ interior (integrableExpSet X μ)
n : ℕ
⊢ 0 ≤ ↑n

Tactic:
by positivity

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

Goal state before:
pp: μ : ℝ
v : ℝ≥0
z : ℂ
hv : ¬v = 0
⊢ 0 ≤ 2 * π * ↑v

Tactic:
by positivity

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
h : 0 ∈ interior (integrableExpSet X μ)
p : ℝ≥0
⊢ MemLp X (↑p) μ

Tactic:
have hX : AEMeasurable X μ := aemeasurable_of_mem_interior_integrableExpSet h
  by_cases hp_zero : p = 0
  · simp only [hp_zero, ENNReal.coe_zero, memLp_zero_iff_aestronglyMeasurable]
    exact hX.aestronglyMeasurable
  rw [← integrable_norm_rpow_iff hX.aestronglyMeasurable (mod_cast hp_zero) (by simp)]
  simp only [norm_eq_abs, ENNReal.coe_toReal]
  exact integrable_rpow_abs_of_mem_interior_integrableExpSet h p.2

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

Goal state before:
pp: m : ℝ
v : ℝ≥0
L : StrongDual ℝ ℝ
⊢ 0 ≤ max (L 1 ^ 2) 0

Tactic:
by positivity

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

Goal state before:
pp: μ : ℝ
v : ℝ≥0
⊢ ∫ (ω : ℝ), ω ^ 2 ∂gaussianReal 0 v = iteratedDeriv 2 (mgf (fun x ↦ x) (gaussianReal 0 v)) 0

Tactic:
rw [iteratedDeriv_mgf_zero]

Goal state after:
μ : ℝ
v : ℝ≥0
⊢ ∫ (ω : ℝ), ω ^ 2 ∂gaussianReal 0 v = ∫ (x : ℝ), ((fun x ↦ x) ^ 2) x ∂gaussianReal 0 v

case h
μ : ℝ
v : ℝ≥0
⊢ 0 ∈ interior (integrableExpSet (fun x ↦ x) (gaussianReal 0 v))
Module: Mathlib.Probability.Distributions.Gaussian.Real

Goal state before:
pp: μ : ℝ
v : ℝ≥0
L : ℝ →ₗ[ℝ] ℝ
⊢ Var[⇑L; gaussianReal μ v] = ↑(L 1 ^ 2).toNNReal * ↑v

Tactic:
rw [← variance_id_map, gaussianReal_map_linearMap, variance_id_gaussianReal]
  · simp only [NNReal.coe_mul, Real.coe_toNNReal']
  · fun_prop

Goal state after:
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
⊢ ‖(toLpₗ μ p) L‖ ≤ ‖L‖ * (eLpNorm id p μ).toReal

Tactic:
simp only [h_Lp, not_false_eq_true, toLpₗ_of_not_memLp, Lp.norm_zero]
    positivity

Goal state after:
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 : ‖(toLpₗ μ p) L‖ ≤ (‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ).toReal ^ p.toReal⁻¹
⊢ 0 ≤ ‖L‖ₑ.toReal ^ p.toReal

Tactic:
by positivity

Goal state after:
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 : ‖(toLpₗ μ p) L‖ ≤ (‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ).toReal ^ p.toReal⁻¹
⊢ 0 ≤ (∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ).toReal

Tactic:
by positivity

Goal state after:
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 : ‖(toLpₗ μ p) L‖ ≤ (‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ).toReal ^ p.toReal⁻¹
⊢ 0 ≤ ‖L‖ₑ.toReal

Tactic:
by positivity

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

Goal state before:
pp: ι : Type u_2
Ω : Type u_3
inst✝¹ : Fintype ι
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : ι → Ω → ℝ
hX : ∀ (i : ι), MemLp (X i) 2 μ
x y : EuclideanSpace ℝ ι
this : ∀ (i : ι), AEMeasurable (X i) μ
⊢ cov[fun ω ↦ ⟪∑ i, ⟪(basisFun ι ℝ) i, x⟫ • (basisFun ι ℝ) i, toLp 2 fun x ↦ X x ω⟫, fun ω ↦
      ⟪∑ i, ⟪(basisFun ι ℝ) i, y⟫ • (basisFun ι ℝ) i, toLp 2 fun x ↦ X x ω⟫; μ] =
    ∑ i, ∑ j, x.ofLp i * y.ofLp j * cov[X i, X j; μ]

Tactic:
simp_rw [sum_inner, real_inner_smul_left, basisFun_inner]
    rw [covariance_fun_sum_fun_sum]
    · refine Finset.sum_congr rfl fun i _ ↦ Finset.sum_congr rfl fun j _ ↦ ?_
      rw [covariance_const_mul_left, covariance_const_mul_right]
      ring
    all_goals exact fun i ↦ (hX i).const_mul _

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

Goal state before:
pp: E : Type u_1
inst✝⁴ : NormedAddCommGroup E
inst✝³ : InnerProductSpace ℝ E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : CompleteSpace E
hμ : ¬MemLp id 2 μ
⊢ covarianceOperator μ = 0

Tactic:
ext x
  refine (unique_continuousLinearMapOfBilin _ fun y ↦ ?_).symm
  simp [hμ, uncenteredCovarianceBilinDual_of_not_memLp]

Goal state after:
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
⊢ 0 ≤ (‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ).toReal ^ p.toReal⁻¹

Tactic:
by positivity

Goal state after:
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
⊢ 0 ≤ (‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ).toReal

Tactic:
by positivity

Goal state after:
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
⊢ 0 ≤ p.toReal⁻¹

Tactic:
by positivity

Goal state after:
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
⊢ 0 ≤ √2

Tactic:
by positivity

Goal state after:
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
⊢ √2 ≠ 0

Tactic:
by positivity

Goal state after:
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
p : E × E
hp1 : ‖p.1 - p.2‖ / √2 ≤ a
hp2 : b < ‖p.1 + p.2‖ / √2
this : b - a < ‖p.1 + p.2‖ / √2 - ‖p.1 - p.2‖ / √2
⊢ 0 ≤ 2

Tactic:
by positivity

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✝ : 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
⊢ 0 ≤ ‖c‖ ^ ↑p

Tactic:
by positivity

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

Goal state before:
pp: a : ℝ
n : ℕ
⊢ 0 ≤ 2

Tactic:
by positivity

Goal state after: