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

Goal state before:
pp: case refine_2
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
Ω'' : Type u_3
mΩ'' : MeasurableSpace Ω''
Y : Ω'' → ℝ
cY : ℝ≥0
inst✝¹ : SFinite ν
η : Kernel (Ω' × Ω) Ω''
inst✝ : IsZeroOrMarkovKernel η
hX : HasSubgaussianMGF X c κ ν
hY : HasSubgaussianMGF Y cY η (ν ⊗ₘ κ)
hκ : IsSFiniteKernel κ
q : ℚ
ω' : Ω'
hX_mgf : ∀ (t : ℝ), mgf X (κ ω') t ≤ rexp (↑c * t ^ 2 / 2)
hX_int : Integrable (fun y ↦ rexp (↑q * X y)) (κ ω')
hY_mgf : ∀ᵐ (b : Ω) ∂κ ω', ∀ (t : ℝ), mgf Y (η (ω', b)) t ≤ rexp (↑cY * t ^ 2 / 2)
h_int_mul : Integrable (fun ω ↦ rexp (↑q * (X ω.1 + Y ω.2))) ((κ ⊗ₖ η) ω')
⊢ (fun x ↦ rexp (↑q * X x) * ∫ (y : Ω''), rexp (↑q * Y y) ∂η (ω', x)) ≤ᵐ[κ ω'] fun x ↦
    rexp (↑q * X x) * rexp (↑cY * ↑q ^ 2 / 2)

Tactic:
·

Goal state after:
case refine_2
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
Ω'' : Type u_3
mΩ'' : MeasurableSpace Ω''
Y : Ω'' → ℝ
cY : ℝ≥0
inst✝¹ : SFinite ν
η : Kernel (Ω' × Ω) Ω''
inst✝ : IsZeroOrMarkovKernel η
hX : HasSubgaussianMGF X c κ ν
hY : HasSubgaussianMGF Y cY η (ν ⊗ₘ κ)
hκ : IsSFiniteKernel κ
q : ℚ
ω' : Ω'
hX_mgf : ∀ (t : ℝ), mgf X (κ ω') t ≤ rexp (↑c * t ^ 2 / 2)
hX_int : Integrable (fun y ↦ rexp (↑q * X y)) (κ ω')
hY_mgf : ∀ᵐ (b : Ω) ∂κ ω', ∀ (t : ℝ), mgf Y (η (ω', b)) t ≤ rexp (↑cY * t ^ 2 / 2)
h_int_mul : Integrable (fun ω ↦ rexp (↑q * (X ω.1 + Y ω.2))) ((κ ⊗ₖ η) ω')
⊢ (fun x ↦ rexp (↑q * X x) * ∫ (y : Ω''), rexp (↑q * Y y) ∂η (ω', x)) ≤ᵐ[κ ω'] fun x ↦
    rexp (↑q * X x) * rexp (↑cY * ↑q ^ 2 / 2)
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: case e_f.e_a
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
j : ℕ
⊢ ∫ (x : ℝ) in 0..↑j, x ^ 2 ∂ρ = ∫ (x : ℝ) in ↑0..↑j, x ^ 2 ∂ρ

pp: case e_f.e_a
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
j : ℕ
⊢ ∀ k < j, IntervalIntegrable (fun x ↦ x ^ 2) ρ ↑k ↑(k + 1)

Tactic:
·

Goal state after:
case e_f.e_a
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
j : ℕ
⊢ ∫ (x : ℝ) in 0..↑j, x ^ 2 ∂ρ = ∫ (x : ℝ) in ↑0..↑j, x ^ 2 ∂ρ
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: case ha
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 := ⋯
ρ : Measure ℝ := ⋯
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0..↑n, x ^ 2 ∂ρ
k : ℕ
a✝ : k ∈ range K
⊢ 0 ≤ ∫ (x : ℝ) in ↑k..↑(k + 1), x ^ 2 ∂ρ

pp: case hbc
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 := ⋯
ρ : Measure ℝ := ⋯
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0..↑n, x ^ 2 ∂ρ
k : ℕ
a✝ : k ∈ range K
⊢ ∑ j ∈ Ioo k K, (↑j ^ 2)⁻¹ ≤ 2 / (↑k + 1)

Tactic:
·

Goal state after:
case ha
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 := ⋯
ρ : Measure ℝ := ⋯
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0..↑n, x ^ 2 ∂ρ
k : ℕ
a✝ : k ∈ range K
⊢ 0 ≤ ∫ (x : ℝ) in ↑k..↑(k + 1), x ^ 2 ∂ρ
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: case hbc
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 := ⋯
ρ : Measure ℝ := ⋯
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0..↑n, x ^ 2 ∂ρ
k : ℕ
a✝ : k ∈ range K
⊢ ∑ j ∈ Ioo k K, (↑j ^ 2)⁻¹ ≤ 2 / (↑k + 1)

Tactic:
·

Goal state after:
case hbc
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 := ⋯
ρ : Measure ℝ := ⋯
Y2 : ∀ (n : ℕ), ∫ (a : Ω), (Y n ^ 2) a = ∫ (x : ℝ) in 0..↑n, x ^ 2 ∂ρ
k : ℕ
a✝ : k ∈ range K
⊢ ∑ j ∈ Ioo k K, (↑j ^ 2)⁻¹ ≤ 2 / (↑k + 1)
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: case h.refine_1
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 : ℕ
a✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ IntegrableOn (fun x ↦ 2 / (↑k + 1) * x ^ 2) (Set.Ioc ↑k ↑(k + 1)) ρ

pp: case h.refine_2
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 : ℕ
a✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ IntegrableOn (HMul.hMul 2) (Set.Ioc ↑k ↑(k + 1)) ρ

pp: case h.refine_3
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 : ℕ
a✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
x : ℝ
hx : x ∈ Set.Ioc ↑k ↑(k + 1)
⊢ 2 / (↑k + 1) * x ^ 2 ≤ 2 * x

Tactic:
·

Goal state after:
case h.refine_1
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 : ℕ
a✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ IntegrableOn (fun x ↦ 2 / (↑k + 1) * x ^ 2) (Set.Ioc ↑k ↑(k + 1)) ρ
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: case h.refine_2
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 : ℕ
a✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ IntegrableOn (HMul.hMul 2) (Set.Ioc ↑k ↑(k + 1)) ρ

pp: case h.refine_3
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 : ℕ
a✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
x : ℝ
hx : x ∈ Set.Ioc ↑k ↑(k + 1)
⊢ 2 / (↑k + 1) * x ^ 2 ≤ 2 * x

Tactic:
·

Goal state after:
case h.refine_2
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 : ℕ
a✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
⊢ IntegrableOn (HMul.hMul 2) (Set.Ioc ↑k ↑(k + 1)) ρ
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: case h.refine_3
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 : ℕ
a✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
x : ℝ
hx : x ∈ Set.Ioc ↑k ↑(k + 1)
⊢ 2 / (↑k + 1) * x ^ 2 ≤ 2 * x

Tactic:
·

Goal state after:
case h.refine_3
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 : ℕ
a✝ : k ∈ range K
Ik : ↑k ≤ ↑(k + 1)
x : ℝ
hx : x ∈ Set.Ioc ↑k ↑(k + 1)
⊢ 2 / (↑k + 1) * x ^ 2 ≤ 2 * x
Module: Mathlib.RepresentationTheory.AlgebraRepresentation.Basic

Goal state before:
pp: case inl
A : Type u_1
V : Type u_2
k : Type u_3
inst✝¹⁰ : Field k
inst✝⁹ : Ring A
inst✝⁸ : Algebra k A
inst✝⁷ : AddCommGroup V
inst✝⁶ : Module k V
inst✝⁵ : Module A V
inst✝⁴ : IsScalarTower k A V
inst✝³ : IsSimpleModule A V
inst✝² : FiniteDimensional k V
inst✝¹ : IsAlgClosed k
inst✝ : IsMulCommutative A
this : Nontrivial V
v : V
v_nz : v ≠ 0
U : Submodule A V :=
  let __src := k ∙ v;
  { toAddSubmonoid := __src.toAddSubmonoid, smul_mem' := ⋯ }
hU : U = ⊥
⊢ Module.finrank k V = 1

pp: case inr
A : Type u_1
V : Type u_2
k : Type u_3
inst✝¹⁰ : Field k
inst✝⁹ : Ring A
inst✝⁸ : Algebra k A
inst✝⁷ : AddCommGroup V
inst✝⁶ : Module k V
inst✝⁵ : Module A V
inst✝⁴ : IsScalarTower k A V
inst✝³ : IsSimpleModule A V
inst✝² : FiniteDimensional k V
inst✝¹ : IsAlgClosed k
inst✝ : IsMulCommutative A
this : Nontrivial V
v : V
v_nz : v ≠ 0
U : Submodule A V :=
  let __src := k ∙ v;
  { toAddSubmonoid := __src.toAddSubmonoid, smul_mem' := ⋯ }
hU : U = ⊤
⊢ Module.finrank k V = 1

Tactic:
·

Goal state after:
case inl
A : Type u_1
V : Type u_2
k : Type u_3
inst✝¹⁰ : Field k
inst✝⁹ : Ring A
inst✝⁸ : Algebra k A
inst✝⁷ : AddCommGroup V
inst✝⁶ : Module k V
inst✝⁵ : Module A V
inst✝⁴ : IsScalarTower k A V
inst✝³ : IsSimpleModule A V
inst✝² : FiniteDimensional k V
inst✝¹ : IsAlgClosed k
inst✝ : IsMulCommutative A
this : Nontrivial V
v : V
v_nz : v ≠ 0
U : Submodule A V :=
  let __src := k ∙ v;
  { toAddSubmonoid := __src.toAddSubmonoid, smul_mem' := ⋯ }
hU : U = ⊥
⊢ Module.finrank k V = 1
Module: Mathlib.RepresentationTheory.AlgebraRepresentation.Basic

Goal state before:
pp: case inr
A : Type u_1
V : Type u_2
k : Type u_3
inst✝¹⁰ : Field k
inst✝⁹ : Ring A
inst✝⁸ : Algebra k A
inst✝⁷ : AddCommGroup V
inst✝⁶ : Module k V
inst✝⁵ : Module A V
inst✝⁴ : IsScalarTower k A V
inst✝³ : IsSimpleModule A V
inst✝² : FiniteDimensional k V
inst✝¹ : IsAlgClosed k
inst✝ : IsMulCommutative A
this : Nontrivial V
v : V
v_nz : v ≠ 0
U : Submodule A V :=
  let __src := k ∙ v;
  { toAddSubmonoid := __src.toAddSubmonoid, smul_mem' := ⋯ }
hU : U = ⊤
⊢ Module.finrank k V = 1

Tactic:
·

Goal state after:
case inr
A : Type u_1
V : Type u_2
k : Type u_3
inst✝¹⁰ : Field k
inst✝⁹ : Ring A
inst✝⁸ : Algebra k A
inst✝⁷ : AddCommGroup V
inst✝⁶ : Module k V
inst✝⁵ : Module A V
inst✝⁴ : IsScalarTower k A V
inst✝³ : IsSimpleModule A V
inst✝² : FiniteDimensional k V
inst✝¹ : IsAlgClosed k
inst✝ : IsMulCommutative A
this : Nontrivial V
v : V
v_nz : v ≠ 0
U : Submodule A V :=
  let __src := k ∙ v;
  { toAddSubmonoid := __src.toAddSubmonoid, smul_mem' := ⋯ }
hU : U = ⊤
⊢ Module.finrank k V = 1
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 : ℕ
x✝ : k < K
⊢ IntervalIntegrable (HMul.hMul 2) ρ ↑k ↑(k + 1)

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, 2 * x ∂ρ = 2 * ∫ (x : ℝ) in 0..↑K, x ∂ρ

Tactic:
·

Goal state after:
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 : ℕ
x✝ : k < K
⊢ IntervalIntegrable (HMul.hMul 2) ρ ↑k ↑(k + 1)
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:
simp [finsuppTensorRight, TensorProduct.finsuppRight_apply_tmul]

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:
refine ⟨fun h ↦ ?_, fun h ↦ ⟨fun t ↦ ?_, fun t ↦ ?_⟩⟩

Goal state after:
case refine_1
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
c : ℝ≥0
hX : AEMeasurable X μ
h : HasSubgaussianMGF id c (Measure.map X μ)
⊢ HasSubgaussianMGF X c μ

case refine_2
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
⊢ Integrable (fun ω ↦ rexp (t * id ω)) (Measure.map X μ)

case refine_3
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
⊢ mgf id (Measure.map X μ) t ≤ rexp (↑c * t ^ 2 / 2)
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case refine_1
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
c : ℝ≥0
hX : AEMeasurable X μ
h : HasSubgaussianMGF id c (Measure.map X μ)
⊢ HasSubgaussianMGF X c μ

pp: case refine_2
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
⊢ Integrable (fun ω ↦ rexp (t * id ω)) (Measure.map X μ)

pp: case refine_3
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
⊢ mgf id (Measure.map X μ) t ≤ rexp (↑c * t ^ 2 / 2)

Tactic:
·

Goal state after:
case refine_1
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
c : ℝ≥0
hX : AEMeasurable X μ
h : HasSubgaussianMGF id c (Measure.map X μ)
⊢ HasSubgaussianMGF X c μ
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case refine_2
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
⊢ Integrable (fun ω ↦ rexp (t * id ω)) (Measure.map X μ)

pp: case refine_3
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
⊢ mgf id (Measure.map X μ) t ≤ rexp (↑c * t ^ 2 / 2)

Tactic:
·

Goal state after:
case refine_2
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
⊢ Integrable (fun ω ↦ rexp (t * id ω)) (Measure.map X μ)
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case refine_3
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
⊢ mgf id (Measure.map X μ) t ≤ rexp (↑c * t ^ 2 / 2)

Tactic:
·

Goal state after:
case refine_3
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
⊢ mgf id (Measure.map X μ) t ≤ rexp (↑c * t ^ 2 / 2)
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), rexp (t * X x) ∂μ ≤ rexp (↑c * t ^ 2 / 2)

pp: 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)

Tactic:
·

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)
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: 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)

Tactic:
·

Goal state after:
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.Moments.SubGaussian

Goal state before:
pp: case c0
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
⊢ 0 ≤ mgf Y μ t

pp: case h₁
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 ≤ rexp (↑cX * t ^ 2 / 2)

pp: case h₂
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 Y μ t ≤ rexp (↑cY * t ^ 2 / 2)

Tactic:
·

Goal state after:
case c0
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
⊢ 0 ≤ mgf Y μ t
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case h₁
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 ≤ rexp (↑cX * t ^ 2 / 2)

pp: case h₂
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 Y μ t ≤ rexp (↑cY * t ^ 2 / 2)

Tactic:
·

Goal state after:
case h₁
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 ≤ rexp (↑cX * t ^ 2 / 2)
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case h₂
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 Y μ t ≤ rexp (↑cY * t ^ 2 / 2)

Tactic:
·

Goal state after:
case h₂
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 Y μ t ≤ rexp (↑cY * t ^ 2 / 2)
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case insert.refine_1
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
h_meas : ∀ (i : ι), AEMeasurable (X i) μ
this : IsProbabilityMeasure μ
i : ι
s : Finset ι
his : i ∉ s
h : (∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ) → HasSubgaussianMGF (fun ω ↦ ∑ i ∈ s, X i ω) (∑ i ∈ s, c i) μ
h_subG : ∀ i_1 ∈ insert i s, HasSubgaussianMGF (X i_1) (c i_1) μ
h_indep' : X i ⟂ᵢ[μ] ∑ j ∈ s, X j
⊢ ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ

pp: case insert.refine_2
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
h_meas : ∀ (i : ι), AEMeasurable (X i) μ
this : IsProbabilityMeasure μ
i : ι
s : Finset ι
his : i ∉ s
h : (∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ) → HasSubgaussianMGF (fun ω ↦ ∑ i ∈ s, X i ω) (∑ i ∈ s, c i) μ
h_subG : ∀ i_1 ∈ insert i s, HasSubgaussianMGF (X i_1) (c i_1) μ
h_indep' : X i ⟂ᵢ[μ] ∑ j ∈ s, X j
⊢ X i ⟂ᵢ[μ] fun ω ↦ ∑ c ∈ s, X c ω

Tactic:
·

Goal state after:
case insert.refine_1
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
h_meas : ∀ (i : ι), AEMeasurable (X i) μ
this : IsProbabilityMeasure μ
i : ι
s : Finset ι
his : i ∉ s
h : (∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ) → HasSubgaussianMGF (fun ω ↦ ∑ i ∈ s, X i ω) (∑ i ∈ s, c i) μ
h_subG : ∀ i_1 ∈ insert i s, HasSubgaussianMGF (X i_1) (c i_1) μ
h_indep' : X i ⟂ᵢ[μ] ∑ j ∈ s, X j
⊢ ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case insert.refine_2
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
h_meas : ∀ (i : ι), AEMeasurable (X i) μ
this : IsProbabilityMeasure μ
i : ι
s : Finset ι
his : i ∉ s
h : (∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ) → HasSubgaussianMGF (fun ω ↦ ∑ i ∈ s, X i ω) (∑ i ∈ s, c i) μ
h_subG : ∀ i_1 ∈ insert i s, HasSubgaussianMGF (X i_1) (c i_1) μ
h_indep' : X i ⟂ᵢ[μ] ∑ j ∈ s, X j
⊢ X i ⟂ᵢ[μ] fun ω ↦ ∑ c ∈ s, X c ω

Tactic:
·

Goal state after:
case insert.refine_2
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
h_meas : ∀ (i : ι), AEMeasurable (X i) μ
this : IsProbabilityMeasure μ
i : ι
s : Finset ι
his : i ∉ s
h : (∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ) → HasSubgaussianMGF (fun ω ↦ ∑ i ∈ s, X i ω) (∑ i ∈ s, c i) μ
h_subG : ∀ i_1 ∈ insert i s, HasSubgaussianMGF (X i_1) (c i_1) μ
h_indep' : X i ⟂ᵢ[μ] ∑ j ∈ s, X j
⊢ X i ⟂ᵢ[μ] fun ω ↦ ∑ c ∈ s, X c ω
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case h_indep
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
s : Finset ι
h_subG : ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
⊢ iIndepFun (fun i ↦ X ↑i) μ

pp: case h_meas
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
s : Finset ι
h_subG : ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
⊢ ∀ (i : ↥s), AEMeasurable (X ↑i) μ

pp: case h_subG
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
s : Finset ι
h_subG : ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
⊢ ∀ i ∈ Finset.univ, HasSubgaussianMGF (X ↑i) (c ↑i) μ

Tactic:
·

Goal state after:
case h_indep
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
s : Finset ι
h_subG : ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
⊢ iIndepFun (fun i ↦ X ↑i) μ
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case h_meas
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
s : Finset ι
h_subG : ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
⊢ ∀ (i : ↥s), AEMeasurable (X ↑i) μ

pp: case h_subG
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
s : Finset ι
h_subG : ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
⊢ ∀ i ∈ Finset.univ, HasSubgaussianMGF (X ↑i) (c ↑i) μ

Tactic:
·

Goal state after:
case h_meas
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
s : Finset ι
h_subG : ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
⊢ ∀ (i : ↥s), AEMeasurable (X ↑i) μ
Module: Mathlib.Probability.Moments.SubGaussian

Goal state before:
pp: case h_subG
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
s : Finset ι
h_subG : ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
⊢ ∀ i ∈ Finset.univ, HasSubgaussianMGF (X ↑i) (c ↑i) μ

Tactic:
·

Goal state after:
case h_subG
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
h_indep : iIndepFun X μ
c : ι → ℝ≥0
s : Finset ι
h_subG : ∀ i ∈ s, HasSubgaussianMGF (X i) (c i) μ
⊢ ∀ i ∈ Finset.univ, HasSubgaussianMGF (X ↑i) (c ↑i) μ