mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.NumberTheory.WellApproximable

Goal state before:
pp: case refine_2
A : Type u_1
inst✝⁵ : NormedAddCommGroup A
inst✝⁴ : CompactSpace A
inst✝³ : PreconnectedSpace A
inst✝² : MeasurableSpace A
inst✝¹ : BorelSpace A
μ : Measure A
inst✝ : μ.IsAddHaarMeasure
ξ : A
n : ℕ
hn : 0 < n
δ : ℝ
hδ : μ univ ≤ (n + 1) • μ (closedBall 0 (δ / 2))
B : ↑(Icc 0 n) → Set A := fun j ↦ closedBall (↑j • ξ) (δ / 2)
hB : ∀ (j : ↑(Icc 0 n)), IsClosed[PseudoMetricSpace.toUniformSpace.toTopologicalSpace] (B j)
this : ¬Pairwise (Disjoint on B)
i j : ↑(Icc 0 n)
hij : i < j
x : A
hx : x ∈ B i ∩ B j
⊢ ‖(↑j - ↑i) • ξ‖ ≤ δ

Tactic:
rw [sub_nsmul _ (Subtype.coe_le_coe.mpr hij.le), ← sub_eq_add_neg, ← dist_eq_norm]

Goal state after:
case refine_2
A : Type u_1
inst✝⁵ : NormedAddCommGroup A
inst✝⁴ : CompactSpace A
inst✝³ : PreconnectedSpace A
inst✝² : MeasurableSpace A
inst✝¹ : BorelSpace A
μ : Measure A
inst✝ : μ.IsAddHaarMeasure
ξ : A
n : ℕ
hn : 0 < n
δ : ℝ
hδ : μ univ ≤ (n + 1) • μ (closedBall 0 (δ / 2))
B : ↑(Icc 0 n) → Set A := fun j ↦ closedBall (↑j • ξ) (δ / 2)
hB : ∀ (j : ↑(Icc 0 n)), IsClosed[PseudoMetricSpace.toUniformSpace.toTopologicalSpace] (B j)
this : ¬Pairwise (Disjoint on B)
i j : ↑(Icc 0 n)
hij : i < j
x : A
hx : x ∈ B i ∩ B j
⊢ dist (↑j • ξ) (↑i • ξ) ≤ δ
Module: Mathlib.Order.Monotone.MonovaryOrder

Goal state before:
pp: ι : Type u_1
α : Type u_3
β : Type u_4
inst✝¹ : LinearOrder α
inst✝ : LinearOrder β
f : ι → α
g : ι → β
s : Set ι
⊢ MonovaryOn f g s ↔ ∃ x, AntitoneOn f s ∧ AntitoneOn g s

Tactic:
by
  simp_rw [← antivaryOn_toDual_left, antivaryOn_iff_exists_monotoneOn_antitoneOn,
    monotoneOn_toDual_comp_iff]

Goal state after:
Module: Mathlib.Order.SaddlePoint

Goal state before:
pp: case left.a
E : Type u_1
F : Type u_2
β : Type u_3
X : Set E
Y : Set F
f : E → F → β
inst✝ : CompleteLinearOrder β
a : E
ha : a ∈ X
b : F
hb : b ∈ Y
h : ⨆ y ∈ Y, f a y = f a b ∧ ⨅ x ∈ X, f x b = f a b
⊢ ⨅ x ∈ X, ⨆ y ∈ Y, f x y ≤ f a b

Tactic:
← h.1

Goal state after:
case left.a
E : Type u_1
F : Type u_2
β : Type u_3
X : Set E
Y : Set F
f : E → F → β
inst✝ : CompleteLinearOrder β
a : E
ha : a ∈ X
b : F
hb : b ∈ Y
h : ⨆ y ∈ Y, f a y = f a b ∧ ⨅ x ∈ X, f x b = f a b
⊢ ⨅ x ∈ X, ⨆ y ∈ Y, f x y ≤ ⨆ y ∈ Y, f a y
Module: Mathlib.Order.Partition.Basic

Goal state before:
pp: α : Type u_1
S : Set (Set α)
u t : Set α
P : Partition u
ht : t ∈ P
hSP : S ⊆ P.parts
⊢ t ⊆ ⋃₀ S ↔ t ∈ S

Tactic:
by
  rw [← subset_sUnion_and_mem_iff_mem hSP]
  simp [ht]

Goal state after:
Module: Mathlib.Order.SaddlePoint

Goal state before:
pp: case right.a
E : Type u_1
F : Type u_2
β : Type u_3
X : Set E
Y : Set F
f : E → F → β
inst✝ : CompleteLinearOrder β
a : E
ha : a ∈ X
b : F
hb : b ∈ Y
h : ⨆ y ∈ Y, f a y = f a b ∧ ⨅ x ∈ X, f x b = f a b
⊢ ⨆ y ∈ Y, ⨅ x ∈ X, f x y ≤ f a b

Tactic:
← h.1

Goal state after:
case right.a
E : Type u_1
F : Type u_2
β : Type u_3
X : Set E
Y : Set F
f : E → F → β
inst✝ : CompleteLinearOrder β
a : E
ha : a ∈ X
b : F
hb : b ∈ Y
h : ⨆ y ∈ Y, f a y = f a b ∧ ⨅ x ∈ X, f x b = f a b
⊢ ⨆ y ∈ Y, ⨅ x ∈ X, f x y ≤ ⨆ y ∈ Y, f a y
Module: Mathlib.Order.Sublocale

Goal state before:
pp: X : Type u_1
inst✝ : Order.Frame X
S : Sublocale X
⊢ range ⇑S.toNucleus = ↑S

Tactic:
ext x
  constructor
  · simp +contextual [eq_comm]
  · intro hx
    exact ⟨x, by simp_all⟩

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

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
ι : Type u_4
inst✝ : LinearOrder ι
τ : Ω → WithTop ι
f : Filtration ι m
hτ : IsStoppingTime f τ
h_countable : (Set.range τ).Countable
i : ι
⊢ MeasurableSet {ω | ↑i ≤ τ ω}

Tactic:
have : {ω | i ≤ τ ω} = {ω | τ ω < i}ᶜ := by
    ext1 ω; simp only [Set.mem_ofPred_eq, Set.mem_compl_iff, not_lt]
  rw [this]
  exact (hτ.measurableSet_lt_of_countable_range h_countable i).compl

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

Goal state before:
pp: case succ
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
ω : Ω
hab : a < b
hω : ∃ k, ∀ (N : ℕ), upcrossingsBefore a b f N ω < k
h₁ : ∀ (a_1 : ℕ), ∃ b, a_1 ≤ b ∧ f b ω < a
h₂ : ∀ (a : ℕ), ∃ b_1, a ≤ b_1 ∧ b < f b_1 ω
k N : ℕ
hN : k ≤ upcrossingsBefore a b f N ω
N₁ : ℕ
hN₁ : N ≤ N₁
hN₁' : f N₁ ω < a
⊢ ∃ N, k + 1 ≤ upcrossingsBefore a b f N ω

Tactic:
obtain ⟨N₂, hN₂, hN₂'⟩ := h₂ N₁

Goal state after:
case succ
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
ω : Ω
hab : a < b
hω : ∃ k, ∀ (N : ℕ), upcrossingsBefore a b f N ω < k
h₁ : ∀ (a_1 : ℕ), ∃ b, a_1 ≤ b ∧ f b ω < a
h₂ : ∀ (a : ℕ), ∃ b_1, a ≤ b_1 ∧ b < f b_1 ω
k N : ℕ
hN : k ≤ upcrossingsBefore a b f N ω
N₁ : ℕ
hN₁ : N ≤ N₁
hN₁' : f N₁ ω < a
N₂ : ℕ
hN₂ : N₁ ≤ N₂
hN₂' : b < f N₂ ω
⊢ ∃ N, k + 1 ≤ upcrossingsBefore a b f N ω
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: case neg
Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝³ : ConditionallyCompleteLinearOrder ι
inst✝² : TopologicalSpace ι
inst✝¹ : OrderTopology ι
inst✝ : FirstCountableTopology ι
f : Filtration ι m
τ : Ω → WithTop ι
hf : f.IsRightContinuous
hτ1 : ∀ (i : ι), MeasurableSet {ω | τ ω < ↑i}
hτ2 : ∀ (i : ι), 𝓝[>] i = ⊥ → MeasurableSet {ω | τ ω = ↑i}
t : ι
ht : ¬𝓝[>] t = ⊥
this : (𝓝[>] t).NeBot
s : ℕ → ι
hs_gt : ∀ (n : ℕ), t < s n
hs_tendsto : Tendsto s atTop (𝓝 t)
h_exists_lt : ∀ (u : ι), t < u → ∃ i, s i < u
h_exists_lt' : ∀ (u : WithTop ι), ↑t < u → ∃ i, ↑(s i) < u
h_eq_iInter : {ω | τ ω ≤ ↑t} = ⋂ m, {ω | τ ω < ↑(s m)}
⊢ MeasurableSet {ω | τ ω ≤ ↑t}

Tactic:
h_eq_iInter

Goal state after:
case neg
Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝³ : ConditionallyCompleteLinearOrder ι
inst✝² : TopologicalSpace ι
inst✝¹ : OrderTopology ι
inst✝ : FirstCountableTopology ι
f : Filtration ι m
τ : Ω → WithTop ι
hf : f.IsRightContinuous
hτ1 : ∀ (i : ι), MeasurableSet {ω | τ ω < ↑i}
hτ2 : ∀ (i : ι), 𝓝[>] i = ⊥ → MeasurableSet {ω | τ ω = ↑i}
t : ι
ht : ¬𝓝[>] t = ⊥
this : (𝓝[>] t).NeBot
s : ℕ → ι
hs_gt : ∀ (n : ℕ), t < s n
hs_tendsto : Tendsto s atTop (𝓝 t)
h_exists_lt : ∀ (u : ι), t < u → ∃ i, s i < u
h_exists_lt' : ∀ (u : WithTop ι), ↑t < u → ∃ i, ↑(s i) < u
h_eq_iInter : {ω | τ ω ≤ ↑t} = ⋂ m, {ω | τ ω < ↑(s m)}
⊢ MeasurableSet (⋂ m, {ω | τ ω < ↑(s m)})
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
ω : Ω
hab : a < b
hn : upcrossingsBefore a b f N ω < n
⊢ stoppedValue f (fun ω ↦ ↑(upperCrossingTime a b f N (n + 1) ω)) ω -
      stoppedValue f (fun ω ↦ ↑(lowerCrossingTime a b f N n ω)) ω =
    0

Tactic:
have : N ≤ upperCrossingTime a b f N n ω := by
    rw [upcrossingsBefore] at hn
    rw [← not_lt]
    exact fun h => not_le.2 hn (le_csSup (upperCrossingTime_lt_bddAbove hab) h)

Goal state after:
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
ω : Ω
hab : a < b
hn : upcrossingsBefore a b f N ω < n
this : N ≤ upperCrossingTime a b f N n ω
⊢ stoppedValue f (fun ω ↦ ↑(upperCrossingTime a b f N (n + 1) ω)) ω -
      stoppedValue f (fun ω ↦ ↑(lowerCrossingTime a b f N n ω)) ω =
    0
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: case mpr
Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝ : Preorder ι
f : Filtration ι m
τ : Ω → WithTop ι
hτ : IsStoppingTime f τ
s : Set Ω
i : ι
this : ∀ (j : WithTop ι), {ω | τ ω = ↑i} ∩ {ω | τ ω ≤ j} = {ω | τ ω = ↑i} ∩ {_ω | ↑i ≤ j}
h : MeasurableSet (s ∩ {ω | τ ω = ↑i})
⊢ MeasurableSet (s ∩ {ω | τ ω = ↑i})

Tactic:
· refine ⟨le_iSup f i _ h, fun j ↦ ?_⟩
    rw [Set.inter_assoc, this]
    by_cases hij : i ≤ j
    · norm_cast
      simp only [hij, Set.ofPred_true, Set.inter_univ]
      exact f.mono hij _ h
    · simp [hij]

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
ω : Ω
⊢ ↑i < τ ω ∨ ↑i = τ ω ↔ τ ω = ↑i ∨ ↑i < τ ω

Tactic:
cases τ ω with
    | top => simp
    | coe a =>
      norm_cast
      rw [@eq_comm _ i, or_comm]

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
h_countable : (Set.range τ).Countable
i : ι
ω : Ω
⊢ ↑i < τ ω ∨ ↑i = τ ω ↔ τ ω = ↑i ∨ ↑i < τ ω

Tactic:
cases τ ω with
    | top => simp
    | coe a =>
      norm_cast
      rw [@eq_comm _ i, or_comm]

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

Goal state before:
pp: 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
ε : ℝ≥0
n : ℕ
⊢ ε • μ {ω | ↑ε ≤ (range (n + 1)).sup' ⋯ fun k ↦ f k ω} ≤
    ENNReal.ofReal
      (∫ (ω : Ω) in {ω | ↑ε ≤ (range (n + 1)).sup' ⋯ fun k ↦ f k ω},
        stoppedValue f (fun ω ↦ ↑(hittingBtwn f {y | ↑ε ≤ y} 0 n ω)) ω ∂μ)

Tactic:
by
  have : ∀ ω, ((ε : ℝ) ≤ (range (n + 1)).sup' nonempty_range_add_one fun k => f k ω) →
      (ε : ℝ) ≤ stoppedValue f (fun ω ↦ (hittingBtwn f {y : ℝ | ε ≤ y} 0 n ω : ℕ)) ω := by
    intro x hx
    simp_rw [le_sup'_iff, mem_range, Nat.lt_succ_iff] at hx
    refine stoppedValue_hittingBtwn_mem ?_
    simp only [Set.mem_Icc, zero_le, true_and, Set.mem_ofPred_eq]
    exact
      let ⟨j, hj₁, hj₂⟩ := hx
      ⟨j, hj₁, hj₂⟩
  have h := setIntegral_ge_of_const_le_real (measurableSet_le measurable_const
    (measurable_range_sup'' fun n _ => (hsub.stronglyMeasurable n).measurable.le (𝒢.le n)))
      (measure_ne_top _ _) this (Integrable.integrableOn (hsub.integrable_stoppedValue
        (hsub.stronglyAdapted.adapted.isStoppingTime_hittingBtwn measurableSet_Ici)
        (mod_cast hittingBtwn_le)))
  rw [ENNReal.le_ofReal_iff_toReal_le, ENNReal.toReal_smul]
  · exact h
  · exact ENNReal.mul_ne_top (by simp) (measure_ne_top _ _)
  · exact le_trans (mul_nonneg ε.coe_nonneg ENNReal.toReal_nonneg) h

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

Goal state before:
pp: case neg
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N : ℕ
ω : Ω
hab : a < b
hN : ¬N = 0
h₁ : ∀ k ∈ Finset.Ico 1 (upcrossingsBefore a b f N ω + 1), {n | upperCrossingTime a b f N n ω < N}.indicator 1 k = 1
⊢ upcrossingsBefore a b f N ω =
    ∑ i ∈ Finset.Ico (Nat.succ 0) (upcrossingsBefore a b f N ω).succ,
        {n | upperCrossingTime a b f N n ω < N}.indicator 1 i +
      ∑ i ∈ Finset.Ico (upcrossingsBefore a b f N ω).succ N.succ, {n | upperCrossingTime a b f N n ω < N}.indicator 1 i

Tactic:
have h₂ : ∀ k ∈ Finset.Ico (upcrossingsBefore a b f N ω + 1) (N + 1),
      {n : ℕ | upperCrossingTime a b f N n ω < N}.indicator 1 k = 0 := by
    rintro k hk
    rw [Finset.mem_Ico, Nat.succ_le_iff] at hk
    rw [Set.indicator_of_notMem]
    simp only [Set.mem_ofPred_eq, not_lt]
    exact (upperCrossingTime_eq_of_upcrossingsBefore_lt hab hk.1).symm.le

Goal state after:
case neg
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N : ℕ
ω : Ω
hab : a < b
hN : ¬N = 0
h₁ : ∀ k ∈ Finset.Ico 1 (upcrossingsBefore a b f N ω + 1), {n | upperCrossingTime a b f N n ω < N}.indicator 1 k = 1
h₂ :
  ∀ k ∈ Finset.Ico (upcrossingsBefore a b f N ω + 1) (N + 1), {n | upperCrossingTime a b f N n ω < N}.indicator 1 k = 0
⊢ upcrossingsBefore a b f N ω =
    ∑ i ∈ Finset.Ico (Nat.succ 0) (upcrossingsBefore a b f N ω).succ,
        {n | upperCrossingTime a b f N n ω < N}.indicator 1 i +
      ∑ i ∈ Finset.Ico (upcrossingsBefore a b f N ω).succ N.succ, {n | upperCrossingTime a b f N n ω < N}.indicator 1 i
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: case pos.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
this : ∀ (N : ℕ), ∫⁻ (ω : Ω), ENNReal.ofReal (f N ω - a)⁺ ∂μ = ENNReal.ofReal (∫ (ω : Ω), (f N ω - a)⁺ ∂μ)
N : ℕ
⊢ Integrable (fun x ↦ ↑↑(upcrossingsBefore a b f N x)) μ

Tactic:
· simp only [NNReal.coe_natCast, hf.stronglyAdapted.integrable_upcrossingsBefore hab]

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

Goal state before:
pp: Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝¹ : Nonempty ι
u : ι → Ω → β
inst✝ : Bot ι
⊢ (stoppedValue u fun x ↦ ⊥) = u ⊥

Tactic:
ext; simp [stoppedValue, ← WithTop.coe_bot]

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

Goal state before:
pp: case neg
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝¹ : Nonempty ι
u : ι → Ω → β
τ σ : Ω → WithTop ι
inst✝ : LinearOrder ι
i : ι
ω : Ω
hτ : ¬τ ω = ⊤
hσ : ¬σ ω = ⊤
hστ : ¬σ ω ≤ τ ω
⊢ u (min (↑(min (↑i) (σ ω)).untopA) (τ ω)).untopA ω = u (min (↑i) ((σ ⊓ τ) ω)).untopA ω

Tactic:
nth_rewrite 2 [untopA_eq_untop]
    · rw [coe_untop, min_assoc, Pi.inf_apply]
    · exact (lt_of_le_of_lt (min_le_right _ _) <| lt_top_iff_ne_top.2 hσ).ne

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
⊢ ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ f n ω) ↔ BddBelow (Set.range fun n ↦ f n ω)

Tactic:
have hup := hf.submartingale.bddAbove_iff_exists_tendsto hbdd

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
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)
⊢ ∀ᵐ (ω : Ω) ∂μ, BddAbove (Set.range fun n ↦ f n ω) ↔ BddBelow (Set.range fun n ↦ f n ω)
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: case inr
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
ω : Ω
i : ι
hi : ↑i = τ ω
hbdd : ↑i ∈ WithTop.some '' ↑s
h : ↑i < ↑n
⊢ u i ω = {a | ↑n ≤ τ a}.indicator (u n) ω + {ω | τ ω = ↑i}.indicator (u i) ω

Tactic:
Set.indicator_of_notMem,

Goal state after:
case inr
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
ω : Ω
i : ι
hi : ↑i = τ ω
hbdd : ↑i ∈ WithTop.some '' ↑s
h : ↑i < ↑n
⊢ u i ω = 0 + {ω | τ ω = ↑i}.indicator (u i) ω

case inr.h
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
ω : Ω
i : ι
hi : ↑i = τ ω
hbdd : ↑i ∈ WithTop.some '' ↑s
h : ↑i < ↑n
⊢ ω ∉ {a | ↑n ≤ τ a}
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
N : ℕ
hbdd : ∀ (ω : Ω), π ω ≤ ↑N
hπ_top : ∀ (ω : Ω), π ω ≠ ⊤
hτ_top : ∀ (ω : Ω), τ ω ≠ ⊤
ω : Ω
⊢ ∑ c ∈ Finset.Ico (untopA (τ ω)) (untopA (π ω)), (u (c + 1) - u c) ω =
    ∑ c ∈ Finset.range (N + 1) with ω ∈ {ω | τ ω ≤ ↑c ∧ ↑c < π ω}, (u (c + 1) - u c) ω

Tactic:
refine Finset.sum_congr ?_ fun _ _ => rfl

Goal state after:
Ω : Type u_1
β : Type u_2
u : ℕ → Ω → β
τ π : Ω → ℕ∞
inst✝ : AddCommGroup β
hle : τ ≤ π
N : ℕ
hbdd : ∀ (ω : Ω), π ω ≤ ↑N
hπ_top : ∀ (ω : Ω), π ω ≠ ⊤
hτ_top : ∀ (ω : Ω), τ ω ≠ ⊤
ω : Ω
⊢ Finset.Ico (untopA (τ ω)) (untopA (π ω)) = {i ∈ Finset.range (N + 1) | ω ∈ {ω | τ ω ≤ ↑i ∧ ↑i < π ω}}
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: case refine_2.refine_3
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
⊢ |(||X ω| ^ p|)| * rexp (v * X ω + x * |X ω|) ≤ |(p / (|t| - x)) ^ p| * rexp (v * X ω + |t| * |X ω|)

Tactic:
abs_rpow_of_nonneg (abs_nonneg _),

Goal state after:
case refine_2.refine_3
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
⊢ |(|(|X ω|)|)| ^ p * rexp (v * X ω + x * |X ω|) ≤ |(p / (|t| - x)) ^ p| * rexp (v * X ω + |t| * |X ω|)
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
⊢ Integrable (fun ω ↦ X ω ^ n * rexp (v * X ω)) μ

Tactic:
convert!
    integrable_rpow_mul_exp_of_integrable_exp_mul ht ht_int_pos ht_int_neg
      (by positivity : 0 ≤ (n : ℝ)) with
    ω

Goal state after:
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
ω : Ω
⊢ X ω ^ n = X ω ^ ↑n
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:

Tactic:
v - ((v - l) ⊓ (u - v)) / 2
    _ ≤ v := by
      rw [sub_le_iff_le_add]
      exact le_add_of_nonneg_right (by positivity)
    _ < u := hv.2

Goal state after:
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'
inst✝ : IsProbabilityMeasure μ
hXY : mgf X μ = mgf Y μ'
⊢ mgf Y μ' 0 ≠ 0

Tactic:
← hXY

Goal state after:
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'
inst✝ : IsProbabilityMeasure μ
hXY : mgf X μ = mgf Y μ'
⊢ mgf X μ 0 ≠ 0
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'
inst✝ : IsProbabilityMeasure μ
hXY : mgf X μ = mgf Y μ'
⊢ Set.EqOn (complexMGF X μ) (complexMGF Y μ') {z | z.re ∈ interior (integrableExpSet X μ)}

Tactic:
by
  refine eqOn_complexMGF_of_mgf' hXY ?_
  simp only [IsProbabilityMeasure.ne_zero, false_iff]
  suffices mgf Y μ' 0 ≠ 0 by
    intro h_contra
    simp [h_contra] at this
  rw [← hXY]
  exact (mgf_pos (by simp)).ne'

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
⊢ max Var[⇑L; μ] 0 = Var[⇑L; μ]

Tactic:
simp only [sup_eq_left]
      exact variance_nonneg _ _

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
⊢ ∫⁻ (x : E), ‖L‖ₑ ^ p.toReal * ‖x‖ₑ ^ p.toReal ∂μ = ‖L‖ₑ ^ p.toReal * ∫⁻ (x : E), ‖x‖ₑ ^ p.toReal ∂μ

Tactic:
by rw [lintegral_const_mul]; fun_prop

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

Goal state before:
pp: E : Type u_1
inst✝² : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝¹ : NormedSpace ℝ E
inst✝ : OpensMeasurableSpace E
h : MemLp id 2 μ
L₁ L₂ : StrongDual ℝ E
x : E
hxL₁ : ↑↑(MemLp.toLp (fun x ↦ L₁ (id x)) ⋯) x = L₁ (id x)
hxL₂ : ↑↑(MemLp.toLp (fun x ↦ L₂ (id x)) ⋯) x = L₂ (id x)
⊢ ↑↑(MemLp.toLp ⇑L₂ ⋯) x * ↑↑(MemLp.toLp ⇑L₁ ⋯) x = L₁ x * L₂ x

Tactic:
simp only [id_eq] at hxL₁ hxL₂

Goal state after:
E : Type u_1
inst✝² : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝¹ : NormedSpace ℝ E
inst✝ : OpensMeasurableSpace E
h : MemLp id 2 μ
L₁ L₂ : StrongDual ℝ E
x : E
hxL₁ : ↑↑(MemLp.toLp (fun x ↦ L₁ x) ⋯) x = L₁ x
hxL₂ : ↑↑(MemLp.toLp (fun x ↦ L₂ x) ⋯) x = L₂ x
⊢ ↑↑(MemLp.toLp ⇑L₂ ⋯) x * ↑↑(MemLp.toLp ⇑L₁ ⋯) x = L₁ x * L₂ x
Module: Mathlib.Probability.Distributions.Fernique

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

Tactic:
normThreshold,

Goal state after:
a : ℝ
n : ℕ
⊢ arithGeom (√2) a a n = a * (1 + √2) * (√2 ^ (n + 1) - 1)
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
μ : Measure E
inst✝ : IsGaussian μ
C C' : ℝ
hint :
  (∀ᵐ (x : E) ∂μ, Integrable (fun y ↦ rexp (C * ‖x + y‖ ^ 2)) (Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)) ∧
    Integrable (fun x ↦ ∫ (y : E), ‖rexp (C * ‖x + y‖ ^ 2)‖ ∂Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ) μ
hC'_pos : 0 < C'
hC'_lt : C' < C
⊢ ∀ᵐ (y : E) ∂μ, Integrable (fun x ↦ rexp (C * ‖x - y‖ ^ 2)) μ

Tactic:
replace hC := hint.1

Goal state after:
E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
μ : Measure E
inst✝ : IsGaussian μ
C C' : ℝ
hint :
  (∀ᵐ (x : E) ∂μ, Integrable (fun y ↦ rexp (C * ‖x + y‖ ^ 2)) (Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)) ∧
    Integrable (fun x ↦ ∫ (y : E), ‖rexp (C * ‖x + y‖ ^ 2)‖ ∂Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ) μ
hC'_pos : 0 < C'
hC'_lt : C' < C
hC : ∀ᵐ (x : E) ∂μ, Integrable (fun y ↦ rexp (C * ‖x + y‖ ^ 2)) (Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)
⊢ ∀ᵐ (y : E) ∂μ, Integrable (fun x ↦ rexp (C * ‖x - y‖ ^ 2)) μ
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
μ : Measure E
inst✝ : IsGaussian μ
C C' : ℝ
hint : Integrable (fun x ↦ rexp (C * ‖x‖ ^ 2)) (μ ∗ Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)
hC'_pos : 0 < C'
hC'_lt : C' < C
h_int : ∀ᵐ (y : E) ∂μ, Integrable (fun x ↦ rexp (C * ‖x - y‖ ^ 2)) μ
y : E
hy : Integrable (fun x ↦ rexp (C * ‖x - y‖ ^ 2)) μ
ε : ℝ := (C - C') / C'
hε : 0 < ε
x : E
⊢ ‖x - y + y‖ ^ 2 ≤ (‖x - y‖ + ‖y‖) ^ 2

Tactic:
grw [norm_add_le (x - y) y]

Goal state after:
Module: Mathlib.Probability.BrownianMotion.GaussianProjectiveFamily

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

Tactic:
by
  rw [projectiveFamily, variance_map_equiv]
  rfl

Goal state after:
Module: Mathlib.Probability.BrownianMotion.GaussianProjectiveFamily

Goal state before:
pp: I : Finset ℝ≥0
s t : ↥I
⊢ Measure.map (fun x ↦ x s - x t) (projectiveFamily I) = gaussianReal 0 (nndist ↑s ↑t)

Tactic:
HasGaussianLaw.map_eq_gaussianReal,

Goal state after:
I : Finset ℝ≥0
s t : ↥I
⊢ gaussianReal (∫ (x : ↥I → ℝ), x s - x t ∂projectiveFamily I) Var[fun x ↦ x s - x t; projectiveFamily I].toNNReal =
    gaussianReal 0 (nndist ↑s ↑t)

I : Finset ℝ≥0
s t : ↥I
⊢ HasGaussianLaw (fun x ↦ x s - x t) (projectiveFamily I)