mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Kernel.Condexp

Goal state before:
pp: case neg.refine_2
Ω : Type u_1
F : Type u_2
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
s : Set Ω
inst✝² : NormedAddCommGroup F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hs : MeasurableSet s
f : Ω → F
hf : Integrable f μ
hμs : ¬μ s = 0
t : Set Ω
ht : MeasurableSet t
⊢ ∫ (x : Ω) in t, ∫ (x : Ω), f x ∂μ[|s] ∂μ.restrict s = ∫ (x : Ω) in t, f x ∂μ.restrict s

Tactic:
obtain (h | h | h | h) := measurableSet_generateFrom_singleton_iff.1 ht

Goal state after:
case neg.refine_2.inl
Ω : Type u_1
F : Type u_2
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
s : Set Ω
inst✝² : NormedAddCommGroup F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hs : MeasurableSet s
f : Ω → F
hf : Integrable f μ
hμs : ¬μ s = 0
t : Set Ω
ht : MeasurableSet t
h : t = ∅
⊢ ∫ (x : Ω) in t, ∫ (x : Ω), f x ∂μ[|s] ∂μ.restrict s = ∫ (x : Ω) in t, f x ∂μ.restrict s

case neg.refine_2.inr.inl
Ω : Type u_1
F : Type u_2
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
s : Set Ω
inst✝² : NormedAddCommGroup F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hs : MeasurableSet s
f : Ω → F
hf : Integrable f μ
hμs : ¬μ s = 0
t : Set Ω
ht : MeasurableSet t
h : t = s
⊢ ∫ (x : Ω) in t, ∫ (x : Ω), f x ∂μ[|s] ∂μ.restrict s = ∫ (x : Ω) in t, f x ∂μ.restrict s

case neg.refine_2.inr.inr.inl
Ω : Type u_1
F : Type u_2
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
s : Set Ω
inst✝² : NormedAddCommGroup F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hs : MeasurableSet s
f : Ω → F
hf : Integrable f μ
hμs : ¬μ s = 0
t : Set Ω
ht : MeasurableSet t
h : t = sᶜ
⊢ ∫ (x : Ω) in t, ∫ (x : Ω), f x ∂μ[|s] ∂μ.restrict s = ∫ (x : Ω) in t, f x ∂μ.restrict s

case neg.refine_2.inr.inr.inr
Ω : Type u_1
F : Type u_2
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
s : Set Ω
inst✝² : NormedAddCommGroup F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hs : MeasurableSet s
f : Ω → F
hf : Integrable f μ
hμs : ¬μ s = 0
t : Set Ω
ht : MeasurableSet t
h : t = univ
⊢ ∫ (x : Ω) in t, ∫ (x : Ω), f x ∂μ[|s] ∂μ.restrict s = ∫ (x : Ω) in t, f x ∂μ.restrict s
Module: Mathlib.Probability.Independence.ZeroOne

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
s : ι → MeasurableSpace Ω
m0 : MeasurableSpace Ω
κ : Kernel α Ω
μα : Measure α
inst✝² : SemilatticeInf ι
inst✝¹ : NoMinOrder ι
inst✝ : Nonempty ι
h_le : ∀ (n : ι), s n ≤ m0
h_indep : iIndep s κ μα
t : Set Ω
ht_tail : MeasurableSet t
⊢ ∀ᵐ (a : α) ∂μα, (κ a) t = 0 ∨ (κ a) t = 1

Tactic:
apply measure_eq_zero_or_one_of_indepSet_self' ?_
    ((indep_limsup_atBot_self h_le h_indep).indepSet_of_measurableSet ht_tail ht_tail)
  filter_upwards [h_indep.ae_isProbabilityMeasure] with a ha using by infer_instance

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

Goal state before:
pp: Ω : Type u_1
E : Type u_2
m : MeasurableSpace Ω
μ : Measure Ω
inst✝¹³ : NormedAddCommGroup E
inst✝¹² : NormedSpace ℝ E
inst✝¹¹ : CompleteSpace E
ι : Type u_3
inst✝¹⁰ : LinearOrder ι
inst✝⁹ : LocallyFiniteOrder ι
inst✝⁸ : OrderBot ι
inst✝⁷ : TopologicalSpace ι
inst✝⁶ : DiscreteTopology ι
inst✝⁵ : MeasurableSpace ι
inst✝⁴ : BorelSpace ι
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
ℱ : Filtration ι m
τ σ : Ω → WithTop ι
f : ι → Ω → E
inst✝ : SigmaFiniteFiltration μ ℱ
h : Martingale f ℱ μ
hτ : IsStoppingTime ℱ τ
hσ : IsStoppingTime ℱ σ
n : ι
hτ_le : ∀ (x : Ω), τ x ≤ ↑n
h_sf_min : SigmaFinite (μ.trim ⋯)
h1 : μ[stoppedValue f τ | hτ.measurableSpace] = stoppedValue f τ
⊢ stoppedValue f τ =ᵐ[μ.restrict {x | τ x ≤ σ x}] μ[stoppedValue f τ | hσ.measurableSpace]

Tactic:
exact (condExp_stoppedValue_stopping_time_ae_eq_restrict_le h hτ hσ hτ_le).symm

Goal state after:
Module: Mathlib.Probability.Independence.Conditional

Goal state before:
pp: Ω : Type u_1
β : Type u_3
β' : Type u_4
mΩ : MeasurableSpace Ω
inst✝⁵ : StandardBorelSpace Ω
μ : Measure Ω
inst✝⁴ : IsFiniteMeasure μ
f : Ω → β
g : Ω → β'
γ : Type u_5
mγ : MeasurableSpace γ
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
inst✝³ : StandardBorelSpace β
inst✝² : Nonempty β
inst✝¹ : StandardBorelSpace β'
inst✝ : Nonempty β'
hf : Measurable f
hg : Measurable g
k : Ω → γ
hk : Measurable k
e : γ × β' × β ≃ᵐ (γ × β') × β := MeasurableEquiv.prodAssoc.symm
h_eq :
  ⇑(Kernel.id ×ₖ condDistrib g k μ ×ₖ condDistrib f k μ) ∘ₘ Measure.map k μ =
    ⇑(Kernel.id ×ₖ Kernel.prodMkRight β' (condDistrib f k μ)) ∘ₘ Measure.map (fun a ↦ (k a, g a)) μ
h1 : Measure.map (fun x ↦ ((k x, g x), f x)) μ = Measure.map (⇑e) (Measure.map (fun a ↦ (k a, g a, f a)) μ)
h1_symm : Measure.map (fun a ↦ (k a, g a, f a)) μ = Measure.map (⇑e.symm) (Measure.map (fun x ↦ ((k x, g x), f x)) μ)
⊢ ⇑(Kernel.id ×ₖ condDistrib g k μ ×ₖ condDistrib f k μ) ∘ₘ Measure.map k μ =
    Measure.map (⇑e) (⇑(Kernel.id ×ₖ (condDistrib g k μ ×ₖ condDistrib f k μ)) ∘ₘ Measure.map k μ)

Tactic:
rw [← Measure.deterministic_comp_eq_map e.measurable, Measure.comp_assoc]

Goal state after:
Ω : Type u_1
β : Type u_3
β' : Type u_4
mΩ : MeasurableSpace Ω
inst✝⁵ : StandardBorelSpace Ω
μ : Measure Ω
inst✝⁴ : IsFiniteMeasure μ
f : Ω → β
g : Ω → β'
γ : Type u_5
mγ : MeasurableSpace γ
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
inst✝³ : StandardBorelSpace β
inst✝² : Nonempty β
inst✝¹ : StandardBorelSpace β'
inst✝ : Nonempty β'
hf : Measurable f
hg : Measurable g
k : Ω → γ
hk : Measurable k
e : γ × β' × β ≃ᵐ (γ × β') × β := MeasurableEquiv.prodAssoc.symm
h_eq :
  ⇑(Kernel.id ×ₖ condDistrib g k μ ×ₖ condDistrib f k μ) ∘ₘ Measure.map k μ =
    ⇑(Kernel.id ×ₖ Kernel.prodMkRight β' (condDistrib f k μ)) ∘ₘ Measure.map (fun a ↦ (k a, g a)) μ
h1 : Measure.map (fun x ↦ ((k x, g x), f x)) μ = Measure.map (⇑e) (Measure.map (fun a ↦ (k a, g a, f a)) μ)
h1_symm : Measure.map (fun a ↦ (k a, g a, f a)) μ = Measure.map (⇑e.symm) (Measure.map (fun x ↦ ((k x, g x), f x)) μ)
⊢ ⇑(Kernel.id ×ₖ condDistrib g k μ ×ₖ condDistrib f k μ) ∘ₘ Measure.map k μ =
    ⇑(Kernel.deterministic ⇑e ⋯ ∘ₖ (Kernel.id ×ₖ (condDistrib g k μ ×ₖ condDistrib f k μ))) ∘ₘ Measure.map k μ
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: Ω : Type u_1
Ω' : Type u_2
mΩ : MeasurableSpace Ω
mΩ' : MeasurableSpace Ω'
ν : Measure Ω'
κ : Kernel Ω' Ω
X : Ω → ℝ
c : ℝ≥0
Y : Ω → ℝ
h : HasSubgaussianMGF X c κ ν
h' : X =ᵐ[⇑κ ∘ₘ ν] Y
t : ℝ
ω : Ω
hω : X ω = Y ω
⊢ rexp (t * Y ω) = rexp (t * X ω)

Tactic:
by rw [hω]

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

Goal state before:
pp: Ω : Type u_1
Ω' : Type u_2
mΩ : MeasurableSpace Ω
mΩ' : MeasurableSpace Ω'
ν : Measure Ω'
κ : Kernel Ω' Ω
X Y : Ω → ℝ
cX cY : ℝ≥0
hX : HasSubgaussianMGF X cX κ ν
hY : HasSubgaussianMGF Y cY κ ν
hX0 : ¬cX = 0
hY0 : ¬cY = 0
p : ℝ≥0 := (NNReal.sqrt cX + NNReal.sqrt cY) / NNReal.sqrt cX
q : ℝ≥0 := (NNReal.sqrt cX + NNReal.sqrt cY) / NNReal.sqrt cY
ω' : Ω'
hmX : ∀ (t : ℝ), mgf X (κ ω') t ≤ rexp (↑cX * t ^ 2 / 2)
hmY : ∀ (t : ℝ), mgf Y (κ ω') t ≤ rexp (↑cY * t ^ 2 / 2)
hlX : ∀ (t : ℝ), MemLp (fun ω ↦ rexp (t * X ω)) (↑p) (κ ω')
hlY : ∀ (t : ℝ), MemLp (fun ω ↦ rexp (t * Y ω)) (↑q) (κ ω')
t : ℝ
⊢ (↑p)⁻¹ + (↑q)⁻¹ = 1⁻¹

Tactic:
by simp [field, p, q]

Goal state after:
Module: Mathlib.RepresentationTheory.Action

Goal state before:
pp: k : Type u
G : Type v
inst✝¹ : Monoid G
inst✝ : Semiring k
X : Type w
g : G
x : X
⊢ ((linearize k G (Action.trivial G X)) g) ((MonoidAlgebra.lsingle x) 1) = (LinearMap.id ∘ₗ MonoidAlgebra.lsingle x) 1

Tactic:
LinearMap.id_comp,

Goal state after:
k : Type u
G : Type v
inst✝¹ : Monoid G
inst✝ : Semiring k
X : Type w
g : G
x : X
⊢ ((linearize k G (Action.trivial G X)) g) ((MonoidAlgebra.lsingle x) 1) = (MonoidAlgebra.lsingle x) 1
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: Ω : Type u_1
m mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
c : ℝ≥0
hm : m ≤ mΩ
hXm : Measurable X
hX : HasSubgaussianMGF X c μ
t : ℝ
⊢ ∫ (x : Ω), (fun ω ↦ rexp (t * X ω)) x ∂μ.trim hm ≤ rexp (↑c * t ^ 2 / 2)

Tactic:
← integral_trim

Goal state after:
Ω : Type u_1
m mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
c : ℝ≥0
hm : m ≤ mΩ
hXm : Measurable X
hX : HasSubgaussianMGF X c μ
t : ℝ
⊢ ∫ (x : Ω), rexp (t * X x) ∂μ ≤ rexp (↑c * t ^ 2 / 2)

case hf
Ω : Type u_1
m mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
c : ℝ≥0
hm : m ≤ mΩ
hXm : Measurable X
hX : HasSubgaussianMGF X c μ
t : ℝ
⊢ StronglyMeasurable fun ω ↦ rexp (t * X ω)
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hindep : Pairwise ((fun f g ↦ f ⟂ᵢ g) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
c : ℝ
c_one : 1 < c
ε : ℝ
εpos : 0 < ε
c_pos : 0 < c
hX : ∀ (i : ℕ), AEStronglyMeasurable (X i) ℙ
A : ∀ (i : ℝ), StronglyMeasurable ((Set.Ioc (-i) i).indicator id)
Y : ℕ → Ω → ℝ := fun n ↦ truncation (X n) ↑n
⊢ ∀ᵐ (ω : Ω),
    ∀ᶠ (n : ℕ) in atTop,
      |∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) (↑i) ω - ∫ (a : Ω), (range ⌊c ^ n⌋₊).sum Y a| < ε * ↑⌊c ^ n⌋₊

Tactic:
set S := fun n => ∑ i ∈ range n, Y i with hS

Goal state after:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hindep : Pairwise ((fun f g ↦ f ⟂ᵢ g) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
c : ℝ
c_one : 1 < c
ε : ℝ
εpos : 0 < ε
c_pos : 0 < c
hX : ∀ (i : ℕ), AEStronglyMeasurable (X i) ℙ
A : ∀ (i : ℝ), StronglyMeasurable ((Set.Ioc (-i) i).indicator id)
Y : ℕ → Ω → ℝ := fun n ↦ truncation (X n) ↑n
S : ℕ → Ω → ℝ := fun n ↦ ∑ i ∈ range n, Y i
hS : S = fun n ↦ ∑ i ∈ range n, Y i
⊢ ∀ᵐ (ω : Ω),
    ∀ᶠ (n : ℕ) in atTop,
      |∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) (↑i) ω - ∫ (a : Ω), (range ⌊c ^ n⌋₊).sum Y a| < ε * ↑⌊c ^ n⌋₊
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hindep : Pairwise ((fun f g ↦ f ⟂ᵢ g) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
c : ℝ
c_one : 1 < c
ε : ℝ
εpos : 0 < ε
c_pos : 0 < c
hX : ∀ (i : ℕ), AEStronglyMeasurable (X i) ℙ
A : ∀ (i : ℝ), StronglyMeasurable ((Set.Ioc (-i) i).indicator id)
Y : ℕ → Ω → ℝ := fun n ↦ truncation (X n) ↑n
S : ℕ → Ω → ℝ := fun n ↦ ∑ i ∈ range n, Y i
hS : S = fun n ↦ ∑ i ∈ range n, Y i
⊢ ∀ᵐ (ω : Ω),
    ∀ᶠ (n : ℕ) in atTop,
      |∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) (↑i) ω - ∫ (a : Ω), (range ⌊c ^ n⌋₊).sum Y a| < ε * ↑⌊c ^ n⌋₊

Tactic:
let u : ℕ → ℕ := fun n => ⌊c ^ n⌋₊

Goal state after:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hindep : Pairwise ((fun f g ↦ f ⟂ᵢ g) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
c : ℝ
c_one : 1 < c
ε : ℝ
εpos : 0 < ε
c_pos : 0 < c
hX : ∀ (i : ℕ), AEStronglyMeasurable (X i) ℙ
A : ∀ (i : ℝ), StronglyMeasurable ((Set.Ioc (-i) i).indicator id)
Y : ℕ → Ω → ℝ := fun n ↦ truncation (X n) ↑n
S : ℕ → Ω → ℝ := fun n ↦ ∑ i ∈ range n, Y i
hS : S = fun n ↦ ∑ i ∈ range n, Y i
u : ℕ → ℕ := fun n ↦ ⌊c ^ n⌋₊
⊢ ∀ᵐ (ω : Ω),
    ∀ᶠ (n : ℕ) in atTop,
      |∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) (↑i) ω - ∫ (a : Ω), (range ⌊c ^ n⌋₊).sum Y a| < ε * ↑⌊c ^ n⌋₊
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : ℕ → Ω → ℝ
h_indep : iIndepFun X μ
c : ℝ≥0
n : ℕ
h_subG : ∀ i < n, HasSubgaussianMGF (X i) c μ
ε : ℝ
hε : 0 ≤ ε
⊢ μ.real {ω | ε ≤ ∑ i ∈ Finset.range n, X i ω} ≤ rexp (-ε ^ 2 / (2 * ↑n * ↑c))

Tactic:
by
  have h := (sum_of_iIndepFun h_indep (c := fun _ ↦ c)
    (s := Finset.range n) (by simpa)).measure_ge_le hε
  simpa [← mul_assoc] using h

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hindep : Pairwise ((fun f g ↦ f ⟂ᵢ g) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
c : ℝ
c_one : 1 < c
ε : ℝ
εpos : 0 < ε
c_pos : 0 < c
hX : ∀ (i : ℕ), AEStronglyMeasurable (X i) ℙ
A : ∀ (i : ℝ), StronglyMeasurable ((Set.Ioc (-i) i).indicator id)
Y : ℕ → Ω → ℝ := fun n ↦ truncation (X n) ↑n
S : ℕ → Ω → ℝ := fun n ↦ ∑ i ∈ range n, Y i
hS : S = fun n ↦ ∑ i ∈ range n, Y i
u : ℕ → ℕ := fun n ↦ ⌊c ^ n⌋₊
u_mono : Monotone u
I1 : ∀ (K : ℕ), ∑ j ∈ range K, (↑j ^ 2)⁻¹ * Var[Y j; ℙ] ≤ 2 * ∫ (a : Ω), X 0 a
C : ℝ := c ^ 5 * (c - 1)⁻¹ ^ 3 * (2 * ∫ (a : Ω), X 0 a)
N : ℕ
⊢ ∑ i ∈ range N, (↑(u i) ^ 2)⁻¹ * Var[S (u i); ℙ] = ∑ i ∈ range N, (↑(u i) ^ 2)⁻¹ * ∑ j ∈ range (u i), Var[Y j; ℙ]

Tactic:
by
        congr 1 with i
        congr 1
        rw [hS, IndepFun.variance_sum]
        · intro j _
          exact (hident j).aestronglyMeasurable_fst.memLp_truncation
        · intro k _ l _ hkl
          exact (hindep hkl).comp (A k).measurable (A l).measurable

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
inst✝ : IsProbabilityMeasure μ
a b : ℝ
hm : AEMeasurable X μ
hb : ∀ᵐ (ω : Ω) ∂μ, X ω ∈ Set.Icc a b
hc : ∫ (x : Ω), X x ∂μ = 0
t : ℝ
⊢ mgf X μ t ≤ rexp (↑((‖b - a‖₊ / 2) ^ 2) * t ^ 2 / 2)

Tactic:
obtain ht | ht | ht := lt_trichotomy 0 t

Goal state after:
case inl
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
inst✝ : IsProbabilityMeasure μ
a b : ℝ
hm : AEMeasurable X μ
hb : ∀ᵐ (ω : Ω) ∂μ, X ω ∈ Set.Icc a b
hc : ∫ (x : Ω), X x ∂μ = 0
t : ℝ
ht : 0 < t
⊢ mgf X μ t ≤ rexp (↑((‖b - a‖₊ / 2) ^ 2) * t ^ 2 / 2)

case inr.inl
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
inst✝ : IsProbabilityMeasure μ
a b : ℝ
hm : AEMeasurable X μ
hb : ∀ᵐ (ω : Ω) ∂μ, X ω ∈ Set.Icc a b
hc : ∫ (x : Ω), X x ∂μ = 0
t : ℝ
ht : 0 = t
⊢ mgf X μ t ≤ rexp (↑((‖b - a‖₊ / 2) ^ 2) * t ^ 2 / 2)

case inr.inr
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
inst✝ : IsProbabilityMeasure μ
a b : ℝ
hm : AEMeasurable X μ
hb : ∀ᵐ (ω : Ω) ∂μ, X ω ∈ Set.Icc a b
hc : ∫ (x : Ω), X x ∂μ = 0
t : ℝ
ht : t < 0
⊢ mgf X μ t ≤ rexp (↑((‖b - a‖₊ / 2) ^ 2) * t ^ 2 / 2)
Module: Mathlib.RepresentationTheory.Intertwining

Goal state before:
pp: A : Type u_1
G : Type u_2
V : Type u_3
inst✝³ : CommSemiring A
inst✝² : Monoid G
inst✝¹ : AddCommMonoid V
inst✝ : Module A V
ρ : Representation A G V
g : G
hg : ∀ (g_1 : G), g_1 * g = g * g_1
g' : G
v : V
⊢ (ρ g) ((ρ g') v) = (ρ g') ((ρ g) v)

Tactic:
← Module.End.mul_apply,

Goal state after:
A : Type u_1
G : Type u_2
V : Type u_3
inst✝³ : CommSemiring A
inst✝² : Monoid G
inst✝¹ : AddCommMonoid V
inst✝ : Module A V
ρ : Representation A G V
g : G
hg : ∀ (g_1 : G), g_1 * g = g * g_1
g' : G
v : V
⊢ (ρ g * ρ g') v = (ρ g') ((ρ g) v)
Module: Mathlib.RepresentationTheory.Intertwining

Goal state before:
pp: A : Type u_1
G : Type u_2
V : Type u_3
inst✝³ : CommSemiring A
inst✝² : Monoid G
inst✝¹ : AddCommMonoid V
inst✝ : Module A V
ρ : Representation A G V
g : G
hg : ∀ (g_1 : G), g_1 * g = g * g_1
g' : G
v : V
⊢ (ρ g * ρ g') v = (ρ g') ((ρ g) v)

Tactic:
← Module.End.mul_apply,

Goal state after:
A : Type u_1
G : Type u_2
V : Type u_3
inst✝³ : CommSemiring A
inst✝² : Monoid G
inst✝¹ : AddCommMonoid V
inst✝ : Module A V
ρ : Representation A G V
g : G
hg : ∀ (g_1 : G), g_1 * g = g * g_1
g' : G
v : V
⊢ (ρ g * ρ g') v = (ρ g' * ρ g) v
Module: Mathlib.RepresentationTheory.Intertwining

Goal state before:
pp: A : Type u_1
G : Type u_2
V : Type u_3
W : Type u_4
U : Type u_5
inst✝⁷ : CommSemiring A
inst✝⁶ : Monoid G
inst✝⁵ : AddCommMonoid V
inst✝⁴ : AddCommMonoid W
inst✝³ : AddCommMonoid U
inst✝² : Module A V
inst✝¹ : Module A W
inst✝ : Module A U
ρ : Representation A G V
σ : Representation A G W
τ : Representation A G U
f : V →ₗ[A] W
z : A[G]
hz : z ∈ Submonoid.center A[G]
x✝ : G
⊢ ρ.asAlgebraHom z ∘ₗ ρ.asAlgebraHom ((MonoidAlgebra.of A G) x✝) =
    ρ.asAlgebraHom ((MonoidAlgebra.of A G) x✝) ∘ₗ ρ.asAlgebraHom z

Tactic:
← Module.End.mul_eq_comp,

Goal state after:
A : Type u_1
G : Type u_2
V : Type u_3
W : Type u_4
U : Type u_5
inst✝⁷ : CommSemiring A
inst✝⁶ : Monoid G
inst✝⁵ : AddCommMonoid V
inst✝⁴ : AddCommMonoid W
inst✝³ : AddCommMonoid U
inst✝² : Module A V
inst✝¹ : Module A W
inst✝ : Module A U
ρ : Representation A G V
σ : Representation A G W
τ : Representation A G U
f : V →ₗ[A] W
z : A[G]
hz : z ∈ Submonoid.center A[G]
x✝ : G
⊢ ρ.asAlgebraHom z * ρ.asAlgebraHom ((MonoidAlgebra.of A G) x✝) =
    ρ.asAlgebraHom ((MonoidAlgebra.of A G) x✝) * ρ.asAlgebraHom z
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hindep : Pairwise ((fun f g ↦ f ⟂ᵢ g) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
c : ℝ
c_one : 1 < c
ε : ℝ
εpos : 0 < ε
c_pos : 0 < c
hX : ∀ (i : ℕ), AEStronglyMeasurable (X i) ℙ
A : ∀ (i : ℝ), StronglyMeasurable ((Set.Ioc (-i) i).indicator id)
Y : ℕ → Ω → ℝ := fun n ↦ truncation (X n) ↑n
S : ℕ → Ω → ℝ := fun n ↦ ∑ i ∈ range n, Y i
hS : S = fun n ↦ ∑ i ∈ range n, Y i
u : ℕ → ℕ := fun n ↦ ⌊c ^ n⌋₊
u_mono : Monotone u
I1 : ∀ (K : ℕ), ∑ j ∈ range K, (↑j ^ 2)⁻¹ * Var[Y j; ℙ] ≤ 2 * ∫ (a : Ω), X 0 a
C : ℝ := c ^ 5 * (c - 1)⁻¹ ^ 3 * (2 * ∫ (a : Ω), X 0 a)
I2 : ∀ (N : ℕ), ∑ i ∈ range N, (↑(u i) ^ 2)⁻¹ * Var[S (u i); ℙ] ≤ C
I3 : ∀ (N : ℕ), ∑ i ∈ range N, ℙ {ω | ↑(u i) * ε ≤ |S (u i) ω - ∫ (a : Ω), S (u i) a|} ≤ ENNReal.ofReal (ε⁻¹ ^ 2 * C)
I4 : ∑' (i : ℕ), ℙ {ω | ↑(u i) * ε ≤ |S (u i) ω - ∫ (a : Ω), S (u i) a|} < ∞
ω : Ω
hω : ∀ᶠ (n : ℕ) in atTop, |∑ c ∈ range (u n), Y c ω - ∫ (a : Ω), ∑ c ∈ range (u n), Y c a| < ε * ↑(u n)
⊢ ∀ᶠ (n : ℕ) in atTop,
    |∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) (↑i) ω - ∫ (a : Ω), (range ⌊c ^ n⌋₊).sum Y a| < ε * ↑⌊c ^ n⌋₊

Tactic:
convert! hω

Goal state after:
case e'_3
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hindep : Pairwise ((fun f g ↦ f ⟂ᵢ g) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
c : ℝ
c_one : 1 < c
ε : ℝ
εpos : 0 < ε
c_pos : 0 < c
hX : ∀ (i : ℕ), AEStronglyMeasurable (X i) ℙ
A : ∀ (i : ℝ), StronglyMeasurable ((Set.Ioc (-i) i).indicator id)
Y : ℕ → Ω → ℝ := fun n ↦ truncation (X n) ↑n
S : ℕ → Ω → ℝ := fun n ↦ ∑ i ∈ range n, Y i
hS : S = fun n ↦ ∑ i ∈ range n, Y i
u : ℕ → ℕ := fun n ↦ ⌊c ^ n⌋₊
u_mono : Monotone u
I1 : ∀ (K : ℕ), ∑ j ∈ range K, (↑j ^ 2)⁻¹ * Var[Y j; ℙ] ≤ 2 * ∫ (a : Ω), X 0 a
C : ℝ := c ^ 5 * (c - 1)⁻¹ ^ 3 * (2 * ∫ (a : Ω), X 0 a)
I2 : ∀ (N : ℕ), ∑ i ∈ range N, (↑(u i) ^ 2)⁻¹ * Var[S (u i); ℙ] ≤ C
I3 : ∀ (N : ℕ), ∑ i ∈ range N, ℙ {ω | ↑(u i) * ε ≤ |S (u i) ω - ∫ (a : Ω), S (u i) a|} ≤ ENNReal.ofReal (ε⁻¹ ^ 2 * C)
I4 : ∑' (i : ℕ), ℙ {ω | ↑(u i) * ε ≤ |S (u i) ω - ∫ (a : Ω), S (u i) a|} < ∞
ω : Ω
hω : ∀ᶠ (n : ℕ) in atTop, |∑ c ∈ range (u n), Y c ω - ∫ (a : Ω), ∑ c ∈ range (u n), Y c a| < ε * ↑(u n)
x✝¹ : ℕ
x✝ : Ω
⊢ (range ⌊c ^ x✝¹⌋₊).sum Y x✝ = ∑ c ∈ range (u x✝¹), Y c x✝
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
A : ∑' (j : ℕ), ℙ {ω | X j ω ∈ Set.Ioi ↑j} < ∞
ω : Ω
hω : ∀ᶠ (n : ℕ) in atTop, X n ω ∉ Set.Ioi ↑n
n : ℕ
hn : X n ω ∉ Set.Ioi ↑n
⊢ n ∈ Set.Ioi 0 → 0 = truncation (X n) (↑n) ω - X n ω

Tactic:
npos

Goal state after:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
A : ∑' (j : ℕ), ℙ {ω | X j ω ∈ Set.Ioi ↑j} < ∞
ω : Ω
hω : ∀ᶠ (n : ℕ) in atTop, X n ω ∉ Set.Ioi ↑n
n : ℕ
hn : X n ω ∉ Set.Ioi ↑n
npos : n ∈ Set.Ioi 0
⊢ 0 = truncation (X n) (↑n) ω - X n ω
Module: Mathlib.RepresentationTheory.Invariants

Goal state before:
pp: k : Type u_1
G : Type u_2
V : Type u_3
inst✝⁵ : CommRing k
inst✝⁴ : Group G
inst✝³ : AddCommGroup V
inst✝² : Module k V
ρ : Representation k G V
inst✝¹ : Fintype G
inst✝ : Invertible ↑(Fintype.card G)
v : V
g : G
⊢ (ρ.asAlgebraHom (single g 1)) ((ρ.asAlgebraHom (average k G)) v) = (ρ.asAlgebraHom (average k G)) v

Tactic:
← Module.End.mul_apply,

Goal state after:
k : Type u_1
G : Type u_2
V : Type u_3
inst✝⁵ : CommRing k
inst✝⁴ : Group G
inst✝³ : AddCommGroup V
inst✝² : Module k V
ρ : Representation k G V
inst✝¹ : Fintype G
inst✝ : Invertible ↑(Fintype.card G)
v : V
g : G
⊢ (ρ.asAlgebraHom (single g 1) * ρ.asAlgebraHom (average k G)) v = (ρ.asAlgebraHom (average k G)) v
Module: Mathlib.RepresentationTheory.Character

Goal state before:
pp: G : Type u_1
k : Type u_2
V : Type u_3
W : Type u_4
inst✝⁷ : Group G
inst✝⁶ : Field k
inst✝⁵ : AddCommGroup V
inst✝⁴ : Module k V
inst✝³ : FiniteDimensional k V
inst✝² : AddCommGroup W
inst✝¹ : Module k W
inst✝ : FiniteDimensional k W
ρ : Representation k G V
σ : Representation k G W
g : G
⊢ (ρ.dual.tprod σ).character g = ρ.character g⁻¹ * σ.character g

Tactic:
char_tensor,

Goal state after:
G : Type u_1
k : Type u_2
V : Type u_3
W : Type u_4
inst✝⁷ : Group G
inst✝⁶ : Field k
inst✝⁵ : AddCommGroup V
inst✝⁴ : Module k V
inst✝³ : FiniteDimensional k V
inst✝² : AddCommGroup W
inst✝¹ : Module k W
inst✝ : FiniteDimensional k W
ρ : Representation k G V
σ : Representation k G W
g : G
⊢ (ρ.dual.character * σ.character) g = ρ.character g⁻¹ * σ.character g
Module: Mathlib.RepresentationTheory.Character

Goal state before:
pp: k : Type u
inst✝¹ : Field k
G : Type v
inst✝ : Group G
V W : FDRep k G
g : G
⊢ (of (dual V.ρ) ⊗ W).character g = V.character g⁻¹ * W.character g

Tactic:
char_tensor,

Goal state after:
k : Type u
inst✝¹ : Field k
G : Type v
inst✝ : Group G
V W : FDRep k G
g : G
⊢ ((of (dual V.ρ)).character * W.character) g = V.character g⁻¹ * W.character g
Module: Mathlib.RepresentationTheory.Coinduced

Goal state before:
pp: k : Type u_1
G : Type u_2
H : Type u_3
inst✝⁶ : Semiring k
inst✝⁵ : Monoid G
inst✝⁴ : Monoid H
φ : G →* H
A : Type u_4
B : Type u_5
inst✝³ : AddCommMonoid A
inst✝² : Module k A
inst✝¹ : AddCommMonoid B
inst✝ : Module k B
σ : Representation k G A
ρ : Representation k G B
f : σ.IntertwiningMap ρ
x : H → A
h : x ∈ coindV φ σ
⊢ (f.compLeft H) x ∈ coindV φ ρ

Tactic:
by
    simp only [mem_coindV, LinearMap.compLeft_apply, Function.comp_apply,
      IntertwiningMap.toLinearMap_apply] at h ⊢
    intro g h0
    simpa [h] using LinearMap.ext_iff.1 (f.2 g) (x h0)

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
E : Type u_2
inst✝⁴ : NormedAddCommGroup E
inst✝³ : NormedSpace ℝ E
inst✝² : CompleteSpace E
inst✝¹ : MeasurableSpace E
inst✝ : BorelSpace E
p : ℝ≥0∞
hp : 1 ≤ p
hp' : p ≠ ∞
X : ℕ → Ω → E
hℒp : MemLp (X 0) p μ
hindep : Pairwise ((fun x1 x2 ↦ x1 ⟂ᵢ[μ] x2) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) μ μ
h : ¬∀ᵐ (ω : Ω) ∂μ, X 0 ω = 0
this : IsProbabilityMeasure μ
hmeas : ∀ (i : ℕ), AEStronglyMeasurable (X i) μ
hint : Integrable (X 0) μ
havg : ∀ (n : ℕ), AEStronglyMeasurable (fun ω ↦ (↑n)⁻¹ • ∑ i ∈ range n, X i ω) μ
n : ℕ
ω : Ω
⊢ (↑n)⁻¹ • ∑ i ∈ range n, X i ω = ((↑n)⁻¹ • ∑ i ∈ range n, X i) ω

Tactic:
simp only [Pi.smul_apply, Finset.sum_apply]

Goal state after:
Module: Mathlib.RepresentationTheory.FiniteIndex

Goal state before:
pp: case inl
k : Type u
G : Type v
inst✝² : CommRing k
inst✝¹ : Group G
S : Subgroup G
inst✝ : DecidableRel ⇑(QuotientGroup.rightRel S)
A : Rep.{w, u, v} k ↥S
g₁ : G
a : ↑A
s s₁ : ↥S
⊢ (A.ρ ⟨s₁ • g₁ * (↑s * g₁)⁻¹, ⋯⟩) ((A.ρ s) a) = (A.ρ ⟨s₁ • g₁ * g₁⁻¹, ⋯⟩) a

Tactic:
← Module.End.mul_apply,

Goal state after:
case inl
k : Type u
G : Type v
inst✝² : CommRing k
inst✝¹ : Group G
S : Subgroup G
inst✝ : DecidableRel ⇑(QuotientGroup.rightRel S)
A : Rep.{w, u, v} k ↥S
g₁ : G
a : ↑A
s s₁ : ↥S
⊢ (A.ρ ⟨s₁ • g₁ * (↑s * g₁)⁻¹, ⋯⟩ * A.ρ s) a = (A.ρ ⟨s₁ • g₁ * g₁⁻¹, ⋯⟩) a