mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
c : ℝ≥0
x✝ : HasSubgaussianMGF X c μ
h1 : ∀ (t : ℝ), Integrable (fun ω ↦ rexp (t * X ω)) μ
h2 : ∀ (t : ℝ), mgf X μ t ≤ rexp (↑c * t ^ 2 / 2)
⊢ ∀ᵐ (ω' : Unit) ∂Measure.dirac (), ∀ (t : ℝ), mgf X ((Kernel.const Unit μ) ω') t ≤ rexp (↑c * t ^ 2 / 2)

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: G : Type v
inst✝⁶ : Monoid G
V : Type v'
inst✝⁵ : AddCommMonoid V
W : Type w'
inst✝⁴ : AddCommMonoid W
k : Type u
inst✝³ : CommSemiring k
inst✝² : Module k V
inst✝¹ : Module k W
σ : Representation k G V
ρ : Representation k G W
α : Type w'
inst✝ : DecidableEq α
f : α →₀ V
w : W
i : α
⊢ ((σ.finsuppTensorLeft ρ α) (f ⊗ₜ[k] w)) i = f i ⊗ₜ[k] w

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: G : Type v
inst✝⁶ : Monoid G
V : Type v'
inst✝⁵ : AddCommMonoid V
W : Type w'
inst✝⁴ : AddCommMonoid W
k : Type u
inst✝³ : CommSemiring k
inst✝² : Module k V
inst✝¹ : Module k W
σ : Representation k G V
ρ : Representation k G W
α : Type w'
inst✝ : DecidableEq α
i : α
v : V
w : W
⊢ (σ.finsuppTensorLeft ρ α).symm (single i (v ⊗ₜ[k] w)) = single i v ⊗ₜ[k] w

Tactic:
by

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
c : ℝ≥0
x✝ : Kernel.HasSubgaussianMGF X c (Kernel.const Unit μ) (Measure.dirac ())
h1 : ∀ (t : ℝ), Integrable (fun ω ↦ rexp (t * X ω)) (⇑(Kernel.const Unit μ) ∘ₘ Measure.dirac ())
h2 : ∀ᵐ (ω' : Unit) ∂Measure.dirac (), ∀ (t : ℝ), mgf X ((Kernel.const Unit μ) ω') t ≤ rexp (↑c * t ^ 2 / 2)
⊢ ∀ (t : ℝ), Integrable (fun ω ↦ rexp (t * X ω)) μ

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: k✝ : Type u
inst✝¹² : Semiring k✝
G : Type v
inst✝¹¹ : Monoid G
V : Type v'
inst✝¹⁰ : AddCommMonoid V
inst✝⁹ : Module k✝ V
W : Type w'
inst✝⁸ : AddCommMonoid W
inst✝⁷ : Module k✝ W
H : Type w
inst✝⁶ : Subsingleton H
inst✝⁵ : MulOneClass H
inst✝⁴ : MulAction G H
k : Type u
inst✝³ : CommSemiring k
inst✝² : Module k V
inst✝¹ : Module k W
σ : Representation k G V
ρ : Representation k G W
α : Type w'
inst✝ : DecidableEq α
g : G
⊢ ↑(TensorProduct.finsuppRight k k V W α) ∘ₗ (σ.tprod (ρ.finsupp α)) g =
    ((σ.tprod ρ).finsupp α) g ∘ₗ ↑(TensorProduct.finsuppRight k k V W α)

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: G : Type v
inst✝⁶ : Monoid G
V : Type v'
inst✝⁵ : AddCommMonoid V
W : Type w'
inst✝⁴ : AddCommMonoid W
k : Type u
inst✝³ : CommSemiring k
inst✝² : Module k V
inst✝¹ : Module k W
σ : Representation k G V
ρ : Representation k G W
α : Type w'
inst✝ : DecidableEq α
v : V
f : α →₀ W
⊢ (σ.finsuppTensorRight ρ α) (v ⊗ₜ[k] f) = f.sum fun i w ↦ single i (v ⊗ₜ[k] w)

Tactic:
by

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
c : ℝ≥0
x✝ : Kernel.HasSubgaussianMGF X c (Kernel.const Unit μ) (Measure.dirac ())
h1 : ∀ (t : ℝ), Integrable (fun ω ↦ rexp (t * X ω)) (⇑(Kernel.const Unit μ) ∘ₘ Measure.dirac ())
h2 : ∀ᵐ (ω' : Unit) ∂Measure.dirac (), ∀ (t : ℝ), mgf X ((Kernel.const Unit μ) ω') t ≤ rexp (↑c * t ^ 2 / 2)
⊢ ∀ (t : ℝ), mgf X μ t ≤ rexp (↑c * t ^ 2 / 2)

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: G : Type v
inst✝⁶ : Monoid G
V : Type v'
inst✝⁵ : AddCommMonoid V
W : Type w'
inst✝⁴ : AddCommMonoid W
k : Type u
inst✝³ : CommSemiring k
inst✝² : Module k V
inst✝¹ : Module k W
σ : Representation k G V
ρ : Representation k G W
α : Type w'
inst✝ : DecidableEq α
v : V
f : α →₀ W
i : α
⊢ ((σ.finsuppTensorRight ρ α) (v ⊗ₜ[k] f)) i = v ⊗ₜ[k] f i

Tactic:
by

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
c : ℝ≥0
h : HasSubgaussianMGF X c μ
⊢ AEStronglyMeasurable X μ

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: G : Type v
inst✝⁶ : Monoid G
V : Type v'
inst✝⁵ : AddCommMonoid V
W : Type w'
inst✝⁴ : AddCommMonoid W
k : Type u
inst✝³ : CommSemiring k
inst✝² : Module k V
inst✝¹ : Module k W
σ : Representation k G V
ρ : Representation k G W
α : Type w'
inst✝ : DecidableEq α
i : α
v : V
w : W
⊢ (σ.finsuppTensorRight ρ α).symm (single i (v ⊗ₜ[k] w)) = v ⊗ₜ[k] single i w

Tactic:
by

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
c : ℝ≥0
h : HasSubgaussianMGF X c μ
Y : Ω → ℝ
h' : X =ᵐ[μ] Y
⊢ HasSubgaussianMGF Y c μ

Tactic:
by

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
c : ℝ≥0
h : HasSubgaussianMGF X c μ
t : ℝ
p : ℝ≥0
⊢ MemLp (fun ω ↦ rexp (t * X ω)) (↑p) μ

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n ↦ truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0..↑n, x ^ 2 ∂ρ
⊢ ∑ k ∈ range K, ∫ (x : ℝ) in ↑k..↑(k + 1), 2 * x ∂ρ = 2 * ∫ (x : ℝ) in 0..↑K, x ∂ρ

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: k✝ : Type u
inst✝¹¹ : Semiring k✝
G : Type v
inst✝¹⁰ : Monoid G
V : Type v'
inst✝⁹ : AddCommMonoid V
inst✝⁸ : Module k✝ V
W : Type w'
inst✝⁷ : AddCommMonoid W
inst✝⁶ : Module k✝ W
H : Type w
inst✝⁵ : Subsingleton H
inst✝⁴ : MulOneClass H
inst✝³ : MulAction G H
k : Type u
inst✝² : CommSemiring k
inst✝¹ : Module k V
inst✝ : Module k W
σ : Representation k G V
ρ : Representation k G W
α : Type w'
g : G
⊢ ↑(TensorProduct.congr (MonoidAlgebra.coeffLinearEquiv k) (MonoidAlgebra.coeffLinearEquiv k) ≪≫ₗ
                finsuppTensorFinsupp' k G α ≪≫ₗ
              Finsupp.domLCongr (Equiv.prodComm G α) ≪≫ₗ
            curryLinearEquiv k ≪≫ₗ
          mapRange.linearEquiv (MonoidAlgebra.coeffLinearEquiv k).symm) ∘ₗ
      ((leftRegular k G).tprod (trivial k G k[α])) g =
    (free k G α) g ∘ₗ
      ↑(TensorProduct.congr (MonoidAlgebra.coeffLinearEquiv k) (MonoidAlgebra.coeffLinearEquiv k) ≪≫ₗ
                finsuppTensorFinsupp' k G α ≪≫ₗ
              Finsupp.domLCongr (Equiv.prodComm G α) ≪≫ₗ
            curryLinearEquiv k ≪≫ₗ
          mapRange.linearEquiv (MonoidAlgebra.coeffLinearEquiv k).symm)

Tactic:
by

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
c : ℝ≥0
h : HasSubgaussianMGF X c μ
t : ℝ
⊢ cgf X μ t ≤ ↑c * t ^ 2 / 2

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsZeroOrProbabilityMeasure μ
⊢ HasSubgaussianMGF (fun x ↦ 0) 0 μ

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: G : Type v
inst✝¹ : Monoid G
k : Type u
inst✝ : CommSemiring k
α : Type w'
g : G
i : α
r s : k
⊢ (leftRegularTensorTrivialIsoFree α) (MonoidAlgebra.single g r ⊗ₜ[k] MonoidAlgebra.single i s) =
    single i (MonoidAlgebra.single g (r * s))

Tactic:
by

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
c : ℝ≥0
h : HasSubgaussianMGF X c μ
⊢ HasSubgaussianMGF (-X) c μ

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: G : Type v
inst✝¹ : Monoid G
k : Type u
inst✝ : CommSemiring k
α : Type w'
i : α
g : G
r : k
⊢ (leftRegularTensorTrivialIsoFree α).symm (single i (MonoidAlgebra.single g r)) =
    MonoidAlgebra.single g 1 ⊗ₜ[k] MonoidAlgebra.single i r

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
c : ℝ≥0
Ω' : Type u_2
mΩ' : MeasurableSpace Ω'
μ : Measure Ω'
Y : Ω' → Ω
X : Ω → ℝ
hY : AEMeasurable Y μ
h : HasSubgaussianMGF X c (Measure.map Y μ)
t : ℝ
h1 : Integrable (fun ω ↦ rexp (t * X ω)) (Measure.map Y μ)
⊢ AEMeasurable Y μ

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
c : ℝ≥0
Ω' : Type u_2
mΩ' : MeasurableSpace Ω'
μ : Measure Ω'
Y : Ω' → Ω
X : Ω → ℝ
hY : AEMeasurable Y μ
h : HasSubgaussianMGF X c (Measure.map Y μ)
t : ℝ
⊢ Integrable (fun ω ↦ rexp (t * (X ∘ Y) ω)) μ

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: k✝ : Type u
inst✝¹¹ : Semiring k✝
G : Type v
inst✝¹⁰ : Monoid G
V : Type v'
inst✝⁹ : AddCommMonoid V
inst✝⁸ : Module k✝ V
W : Type w'
inst✝⁷ : AddCommMonoid W
inst✝⁶ : Module k✝ W
H : Type w
inst✝⁵ : Subsingleton H
inst✝⁴ : MulOneClass H
inst✝³ : MulAction G H
k : Type u
inst✝² : CommSemiring k
inst✝¹ : Module k V
inst✝ : Module k W
σ : Representation k G V
ρ : Representation k G W
v : V
g : G
⊢ (((Finsupp.llift V k k G) fun g ↦ (σ g) v) ∘ₗ ↑(MonoidAlgebra.coeffLinearEquiv k)) ∘ₗ (leftRegular k G) g =
    σ g ∘ₗ ((Finsupp.llift V k k G) fun g ↦ (σ g) v) ∘ₗ ↑(MonoidAlgebra.coeffLinearEquiv k)

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
c : ℝ≥0
Ω' : Type u_2
mΩ' : MeasurableSpace Ω'
μ : Measure Ω'
Y : Ω' → Ω
X : Ω → ℝ
hY : AEMeasurable Y μ
h : HasSubgaussianMGF X c (Measure.map Y μ)
t : ℝ
⊢ mgf (X ∘ Y) μ t ≤ rexp (↑c * t ^ 2 / 2)

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n ↦ truncation X ↑n
ρ : Measure ℝ := Measure.map X ℙ
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0..↑n, x ^ 2 ∂ρ
⊢ ∫ (x : ℝ) in 0..↑K, x ∂ρ ≤ ∫ (a : Ω), X a

Tactic:
by

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
c : ℝ≥0
hX : AEMeasurable X μ
h : HasSubgaussianMGF X c μ
t : ℝ
⊢ AEStronglyMeasurable (fun ω ↦ rexp (t * id ω)) (Measure.map X μ)

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
⊢ ∑ j ∈ range K, (↑j ^ 2)⁻¹ * ∫ (a : Ω), (truncation X ↑j ^ 2) a ≤ 2 * ∫ (a : Ω), X a

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: k✝ : Type u
inst✝¹¹ : Semiring k✝
G : Type v
inst✝¹⁰ : Monoid G
V : Type v'
inst✝⁹ : AddCommMonoid V
inst✝⁸ : Module k✝ V
W : Type w'
inst✝⁷ : AddCommMonoid W
inst✝⁶ : Module k✝ W
H : Type w
inst✝⁵ : Subsingleton H
inst✝⁴ : MulOneClass H
inst✝³ : MulAction G H
k : Type u
inst✝² : CommSemiring k
inst✝¹ : Module k V
inst✝ : Module k W
σ : Representation k G V
ρ : Representation k G W
x : (leftRegular k G).IntertwiningMap σ
⊢ (fun v ↦
        { toLinearMap := ((Finsupp.llift V k k G) fun g ↦ (σ g) v) ∘ₗ ↑(MonoidAlgebra.coeffLinearEquiv k),
          isIntertwining' := ⋯ })
      ((fun f ↦ (Finsupp.llift V k k G).symm (f.toLinearMap ∘ₗ ↑(MonoidAlgebra.coeffLinearEquiv k).symm) 1) x) =
    x

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: k✝ : Type u
inst✝¹¹ : Semiring k✝
G : Type v
inst✝¹⁰ : Monoid G
V : Type v'
inst✝⁹ : AddCommMonoid V
inst✝⁸ : Module k✝ V
W : Type w'
inst✝⁷ : AddCommMonoid W
inst✝⁶ : Module k✝ W
H : Type w
inst✝⁵ : Subsingleton H
inst✝⁴ : MulOneClass H
inst✝³ : MulAction G H
k : Type u
inst✝² : CommSemiring k
inst✝¹ : Module k V
inst✝ : Module k W
σ : Representation k G V
ρ : Representation k G W
v : V
⊢ (fun f ↦ (Finsupp.llift V k k G).symm (f.toLinearMap ∘ₗ ↑(MonoidAlgebra.coeffLinearEquiv k).symm) 1)
      ((fun v ↦
          { toLinearMap := ((Finsupp.llift V k k G) fun g ↦ (σ g) v) ∘ₗ ↑(MonoidAlgebra.coeffLinearEquiv k),
            isIntertwining' := ⋯ })
        v) =
    v

Tactic:
by

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
c : ℝ≥0
hX : AEMeasurable X μ
⊢ HasSubgaussianMGF id c (Measure.map X μ) ↔ HasSubgaussianMGF X c μ

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: G : Type v
inst✝³ : Monoid G
V : Type v'
inst✝² : AddCommMonoid V
k : Type u
inst✝¹ : CommSemiring k
inst✝ : Module k V
σ : Representation k G V
g : G
v : V
⊢ (σ.leftRegularMapEquiv.symm v) (MonoidAlgebra.single g 1) = (σ g) v

Tactic:
by

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
c : ℝ≥0
Ω' : Type u_2
mΩ' : MeasurableSpace Ω'
μ' : Measure Ω'
Y : Ω' → ℝ
hX : HasSubgaussianMGF X c μ
hXY : IdentDistrib X Y μ μ'
⊢ HasSubgaussianMGF Y c μ'

Tactic:
by

Goal state after:
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
⊢ Measurable fun ω ↦ rexp (t * X ω)

Tactic:
by

Goal state after:
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
⊢ Integrable (fun ω ↦ rexp (t * X ω)) (μ.trim hm)

Tactic:
by

Goal state after:
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
⊢ mgf X (μ.trim hm) t ≤ rexp (↑c * t ^ 2 / 2)

Tactic:
by

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
c : ℝ≥0
h : HasSubgaussianMGF X c μ
r : ℝ
⊢ HasSubgaussianMGF (fun ω ↦ r * X ω) (⟨r ^ 2, ⋯⟩ * c) μ

Tactic:
by

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
c : ℝ≥0
h : HasSubgaussianMGF X c μ
r : ℝ
⊢ HasSubgaussianMGF (fun ω ↦ r * X ω) (⟨r ^ 2, ⋯⟩ * c) μ

Tactic:
by
  rw [HasSubgaussianMGF_iff_kernel] at h ⊢
  exact Kernel.HasSubgaussianMGF.const_mul h r

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
c : ℝ≥0
hX : HasSubgaussianMGF X c μ
⊢ integrableExpSet X μ = Set.univ

Tactic:
by

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
c : ℝ≥0
hX : HasSubgaussianMGF X c μ
p : ℝ≥0
⊢ 0 ∈ interior (integrableExpSet X μ)

Tactic:
by

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
c : ℝ≥0
hX : HasSubgaussianMGF X c μ
⊢ 0 ∈ interior (integrableExpSet X μ)

Tactic:
by

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
c : ℝ≥0
h : HasSubgaussianMGF X c μ
ε : ℝ
hε : 0 ≤ ε
⊢ μ.real {ω | ε ≤ X ω} ≤ rexp (-ε ^ 2 / (2 * ↑c))

Tactic:
by

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
h : HasSubgaussianMGF X 0 μ
⊢ X =ᵐ[μ] 0

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X Y : Ω → ℝ
cX cY : ℝ≥0
hX : HasSubgaussianMGF X cX μ
hY : HasSubgaussianMGF Y cY μ
this :
  Kernel.HasSubgaussianMGF (fun ω ↦ X ω + Y ω) ((NNReal.sqrt cX + NNReal.sqrt cY) ^ 2) (Kernel.const Unit μ)
    (Measure.dirac ())
⊢ HasSubgaussianMGF (fun ω ↦ X ω + Y ω) ((NNReal.sqrt cX + NNReal.sqrt cY) ^ 2) μ

Tactic:
simpa [HasSubgaussianMGF_iff_kernel] using this

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X Y : Ω → ℝ
cX cY : ℝ≥0
hX : HasSubgaussianMGF X cX μ
hY : HasSubgaussianMGF Y cY μ
⊢ HasSubgaussianMGF (fun ω ↦ X ω + Y ω) ((NNReal.sqrt cX + NNReal.sqrt cY) ^ 2) μ

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X Y : Ω → ℝ
cX cY : ℝ≥0
hX : HasSubgaussianMGF X cX μ
hY : HasSubgaussianMGF Y cY μ
hindep : X ⟂ᵢ[μ] Y
t : ℝ
⊢ Integrable (fun ω ↦ rexp (t * (X ω + Y ω))) μ

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X Y : Ω → ℝ
cX cY : ℝ≥0
hX : HasSubgaussianMGF X cX μ
hY : HasSubgaussianMGF Y cY μ
hindep : X ⟂ᵢ[μ] Y
t : ℝ
⊢ mgf X μ t * mgf Y μ t ≤ rexp (↑cX * t ^ 2 / 2) * rexp (↑cY * t ^ 2 / 2)

Tactic:
by

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
K : ℕ
⊢ ∑ j ∈ range K, (↑j ^ 2)⁻¹ * Var[Y j; ℙ] ≤ ∑ j ∈ range K, (↑j ^ 2)⁻¹ * ∫ (a : Ω), (truncation (X 0) ↑j ^ 2) a

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X Y : Ω → ℝ
cX cY : ℝ≥0
hX : HasSubgaussianMGF X cX μ
hY : HasSubgaussianMGF Y cY μ
hindep : X ⟂ᵢ[μ] Y
t : ℝ
⊢ rexp (↑cX * t ^ 2 / 2) * rexp (↑cY * t ^ 2 / 2) = rexp ((↑cX + ↑cY) * t ^ 2 / 2)

Tactic:
by

Goal state after:
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 : Semiring 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
hf : ∀ (g : G) (v : V), f ((ρ g) v) = (σ g) (f v)
g : G
⊢ f ∘ₗ ρ g = σ g ∘ₗ f

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X Y : Ω → ℝ
cX cY : ℝ≥0
hX : HasSubgaussianMGF X cX μ
hY : HasSubgaussianMGF Y cY μ
hindep : X ⟂ᵢ[μ] Y
t : ℝ
⊢ mgf (fun ω ↦ X ω + Y ω) μ t ≤ rexp (↑(cX + cY) * t ^ 2 / 2)

Tactic:
by

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
⊢ ∀ (K : ℕ), ∑ j ∈ range K, (↑j ^ 2)⁻¹ * Var[Y j; ℙ] ≤ 2 * ∫ (a : Ω), X 0 a

Tactic:
by

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X Y : Ω → ℝ
cX cY : ℝ≥0
hX : HasSubgaussianMGF X cX μ
hY : HasSubgaussianMGF Y cY μ
hindep : X ⟂ᵢ[μ] Y
⊢ HasSubgaussianMGF (fun ω ↦ X ω - Y ω) (cX + cY) μ

Tactic:
by

Goal state after:
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 : Semiring 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
f : ρ.IntertwiningMap σ
g : G
l : U →ₗ[A] V
⊢ f.toLinearMap ∘ₗ ρ g ∘ₗ l = σ g ∘ₗ f.toLinearMap ∘ₗ l

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Intertwining

Goal state before:
pp: A : Type u_1
G : Type u_2
V : Type u_3
W : Type u_4
inst✝⁵ : Semiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid V
inst✝² : AddCommMonoid W
inst✝¹ : Module A V
inst✝ : Module A W
ρ : Representation A G V
σ : Representation A G W
f g : ρ.IntertwiningMap σ
h : f.toLinearMap = g.toLinearMap
⊢ f = g

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Intertwining

Goal state before:
pp: A : Type u_1
G : Type u_2
V : Type u_3
W : Type u_4
inst✝⁵ : Semiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid V
inst✝² : AddCommMonoid W
inst✝¹ : Module A V
inst✝ : Module A W
ρ : Representation A G V
σ : Representation A G W
⊢ Function.Injective fun f ↦ f.toFun

Tactic:
by

Goal state after:
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 : Semiring 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
⊢ ∀ (g : G), 0 ∘ₗ ρ g = σ g ∘ₗ 0

Tactic:
by

Goal state after:
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 : Semiring 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
f g : ρ.IntertwiningMap σ
⊢ ∀ (g_1 : G), (f.toLinearMap + g.toLinearMap) ∘ₗ ρ g_1 = σ g_1 ∘ₗ (f.toLinearMap + g.toLinearMap)

Tactic:
by

Goal state after:
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 : Semiring 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
n : ℕ
f : ρ.IntertwiningMap σ
⊢ ∀ (g : G), (n • f.toLinearMap) ∘ₗ ρ g = σ g ∘ₗ (n • f.toLinearMap)

Tactic:
by

Goal state after:
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 : Semiring 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
⊢ ∀ (x : ρ.IntertwiningMap σ) (n : ℕ), ⇑(n • x) = n • ⇑x

Tactic:
by

Goal state after:
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 : Semiring 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
f : ρ.IntertwiningMap σ
g : G
w : W
x✝ : w ∈ f.range
v : V
hv : f.toLinearMap v = w
⊢ f.toLinearMap ((ρ g) v) = (σ g) w

Tactic:
by

Goal state after: