mathlib-initiative/mathlib-tactics huggingface dataset:
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
h✝ : HasSubgaussianMGF X c κ ν
ε : ℝ
hε : 0 ≤ ε
hc0 : ¬c = 0
ω' : Ω'
h : ∀ (t : ℝ), 0 ≤ t → (κ ω').real {ω | ε ≤ X ω} ≤ rexp (-t * ε + ↑c * t ^ 2 / 2)
⊢ rexp (-(ε / ↑c) * ε + ↑c * (ε / ↑c) ^ 2 / 2) = rexp (-ε ^ 2 / (2 * ↑c))

Tactic:
by

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 : Ω → ℝ
c : ℝ≥0
h : HasSubgaussianMGF X c κ ν
ε : ℝ
hε : 0 ≤ ε
⊢ ∀ᵐ (ω' : Ω') ∂ν, (κ ω').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
Ω' : Type u_2
mΩ : MeasurableSpace Ω
mΩ' : MeasurableSpace Ω'
ν : Measure Ω'
κ : Kernel Ω' Ω
X : Ω → ℝ
h : HasSubgaussianMGF X 0 κ ν
⊢ {ω | 0 < X ω} = ⋃ ε, {ω | ↑↑ε ≤ X ω}

Tactic:
by

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

Goal state before:
pp: ι : Type u_1
Ω : Type u_2
E : Type u_3
mΩ : MeasurableSpace Ω
P : Measure Ω
inst✝⁴ : LinearOrder ι
𝓕 : Filtration ι mΩ
p : (ι → Ω → E) → Prop
inst✝³ : OrderBot ι
inst✝² : Zero E
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
hp : IsStable 𝓕 p
⊢ IsStable 𝓕 fun Y ↦ Locally p 𝓕 Y P

Tactic:
by

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 : Ω → ℝ
h : HasSubgaussianMGF X 0 κ ν
hs : {ω | 0 < X ω} = ⋃ ε, {ω | ↑↑ε ≤ X ω}
ε : ℚ
ω' : Ω'
a✝ : IsFiniteMeasure (κ ω')
hε : 0 < ε
hm : ∀ (t : ℝ), 0 ≤ t → (κ ω').real {ω | ↑ε ≤ X ω} ≤ rexp (-(t * ↑ε))
this : (κ ω').real {ω | ↑ε ≤ X ω} = 0
⊢ (κ ω') {ω | ↑ε ≤ X ω} = 0

Tactic:
by

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 : Ω → ℝ
h : HasSubgaussianMGF X 0 κ ν
hs : {ω | 0 < X ω} = ⋃ ε, {ω | ↑↑ε ≤ X ω}
ε : ℚ
ω' : Ω'
a✝ : IsFiniteMeasure (κ ω')
hε : 0 < ε
hm : ∀ (t : ℝ), 0 ≤ t → (κ ω').real {ω | ↑ε ≤ X ω} ≤ rexp (-(t * ↑ε))
⊢ Filter.Tendsto (fun t ↦ rexp (-(t * ↑ε))) Filter.atTop (𝓝 0)

Tactic:
by

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

Goal state before:
pp: ι : Type u_1
Ω : Type u_2
E : Type u_3
mΩ : MeasurableSpace Ω
P : Measure Ω
inst✝⁴ : LinearOrder ι
𝓕 : Filtration ι mΩ
X : ι → Ω → E
p q : (ι → Ω → E) → Prop
inst✝³ : OrderBot ι
inst✝² : Zero E
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
hp : IsStable 𝓕 p
hq : IsStable 𝓕 q
x✝ : Locally p 𝓕 X P ∧ Locally q 𝓕 X P
hpX : Locally p 𝓕 X P
hqX : Locally q 𝓕 X P
n : ℕ
this :
  ∀ (p q : (ι → Ω → E) → Prop),
    IsStable 𝓕 p →
      IsStable 𝓕 q →
        ∀ (hpX : Locally p 𝓕 X P) (hqX : Locally q 𝓕 X P),
          p
            (stoppedProcess (fun i ↦ {ω | ⊥ < (hpX.localSeq ⊓ hqX.localSeq) n ω}.indicator (X i))
              ((hpX.localSeq ⊓ hqX.localSeq) n))
⊢ (fun Y ↦ p Y ∧ q Y)
    (stoppedProcess (fun i ↦ {ω | ⊥ < (hpX.localSeq ⊓ hqX.localSeq) n ω}.indicator (X i))
      ((hpX.localSeq ⊓ hqX.localSeq) n))

Tactic:
by

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 : Ω → ℝ
h : HasSubgaussianMGF X 0 κ ν
hs : {ω | 0 < X ω} = ⋃ ε, {ω | ↑↑ε ≤ X ω}
ε : ℚ
⊢ ∀ᵐ (ω' : Ω') ∂ν, 0 < ε → (κ ω') {ω | ↑ε ≤ X ω} = 0

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
inst✝³ : Semiring A
inst✝² : Monoid G
inst✝¹ : AddCommMonoid W
inst✝ : Module A W
ρ : Representation A G W
⊢ Function.Injective toSubmodule

Tactic:
by

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 : Ω → ℝ
h : HasSubgaussianMGF X 0 κ ν
⊢ ∀ᵐ (ω' : Ω') ∂ν, (κ ω') {ω | 0 < X ω} = 0

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : Semiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
ρ' : Subrepresentation ρ
⊢ (ρ 1).restrict ⋯ = 1

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : Semiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
ρ' : Subrepresentation ρ
x y : G
⊢ (ρ (x * y)).restrict ⋯ = (ρ x).restrict ⋯ * (ρ y).restrict ⋯

Tactic:
by

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 : Ω → ℝ
h : HasSubgaussianMGF X 0 κ ν
ω' : Ω'
h2 : (κ ω') {ω | 0 < X ω} = 0
h1 : (κ ω') {ω | X ω < 0} = 0
⊢ (κ ω') {ω | X ω ≠ 0} = (κ ω') {ω | X ω < 0 ∨ 0 < X ω}

Tactic:
by

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 : Ω → ℝ
h : HasSubgaussianMGF X 0 κ ν
ω' : Ω'
h2 : (κ ω') {ω | 0 < X ω} = 0
h1 : (κ ω') {ω | X ω < 0} = 0
⊢ (κ ω') {ω | X ω < 0} + (κ ω') {ω | 0 < X ω} = 0

Tactic:
by

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 : Ω → ℝ
h : HasSubgaussianMGF X 0 κ ν
⊢ ∀ᵐ (ω' : Ω') ∂ν, X =ᵐ[κ ω'] 0

Tactic:
by

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 : Ω → ℝ
hX : Measurable X
h : HasSubgaussianMGF X 0 κ ν
⊢ Measurable 0

Tactic:
by

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 : Ω → ℝ
hX : Measurable X
h : HasSubgaussianMGF X 0 κ ν
⊢ X =ᵐ[⇑κ ∘ₘ ν] 0

Tactic:
by

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 : Ω → ℝ
h : HasSubgaussianMGF X 0 κ ν
⊢ X =ᵐ[⇑κ ∘ₘ ν] 0

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : Semiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
ρ₁ ρ₂ : Subrepresentation ρ
⊢ ∀ (g : G) ⦃v : W⦄, v ∈ ρ₁.toSubmodule ⊔ ρ₂.toSubmodule → (ρ g) v ∈ ρ₁.toSubmodule ⊔ ρ₂.toSubmodule

Tactic:
by

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
hY : HasSubgaussianMGF Y cY κ ν
hX0✝ : cX = 0
hX : HasSubgaussianMGF X 0 κ ν
ω : Ω
hX0 : X ω = 0 ω
⊢ Y ω = X ω + Y ω

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : Semiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
ρ₁ ρ₂ : Subrepresentation ρ
⊢ ∀ (g : G) ⦃v : W⦄, v ∈ ρ₁.toSubmodule ⊓ ρ₂.toSubmodule → (ρ g) v ∈ ρ₁.toSubmodule ⊓ ρ₂.toSubmodule

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : Semiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
⊢ ∀ (g : G) ⦃v : W⦄, v ∈ ⊤ → (ρ g) v ∈ ⊤

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : Semiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
⊢ ∀ (g : G) ⦃v : W⦄, v ∈ ⊥ → (ρ g) v ∈ ⊥

Tactic:
by

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
hX0 : ¬cX = 0
hY0✝ : cY = 0
hY : HasSubgaussianMGF Y 0 κ ν
ω : Ω
hY0 : Y ω = 0 ω
⊢ X ω = X ω + Y ω

Tactic:
by

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

Goal state before:
pp: ι : Type u_1
Ω : Type u_2
E : Type u_3
mΩ : MeasurableSpace Ω
P : Measure Ω
inst✝⁴ : LinearOrder ι
𝓕 : Filtration ι mΩ
X : ι → Ω → E
p✝ q✝ : (ι → Ω → E) → Prop
inst✝³ : OrderBot ι
inst✝² : Zero E
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
hp✝ : IsStable 𝓕 p✝
hq✝ : IsStable 𝓕 q✝
x✝ : Locally p✝ 𝓕 X P ∧ Locally q✝ 𝓕 X P
hpX✝ : Locally p✝ 𝓕 X P
hqX✝ : Locally q✝ 𝓕 X P
n : ℕ
p q : (ι → Ω → E) → Prop
hp : IsStable 𝓕 p
hq : IsStable 𝓕 q
hpX : Locally p 𝓕 X P
hqX : Locally q 𝓕 X P
i : ι
ω : Ω
⊢ {ω | ⊥ < hpX.localSeq n ω ∧ ⊥ < hqX.localSeq n ω}.indicator
      (stoppedProcess (stoppedProcess X (hpX.localSeq n)) (hqX.localSeq n) i) ω =
    {ω | ⊥ < hqX.localSeq n ω}.indicator
      ({ω | ⊥ < hpX.localSeq n ω}.indicator (stoppedProcess (stoppedProcess X (hpX.localSeq n)) (hqX.localSeq n) i)) ω

Tactic:
← stoppedProcess_indicator_comm,

Goal state after:
ι : Type u_1
Ω : Type u_2
E : Type u_3
mΩ : MeasurableSpace Ω
P : Measure Ω
inst✝⁴ : LinearOrder ι
𝓕 : Filtration ι mΩ
X : ι → Ω → E
p✝ q✝ : (ι → Ω → E) → Prop
inst✝³ : OrderBot ι
inst✝² : Zero E
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
hp✝ : IsStable 𝓕 p✝
hq✝ : IsStable 𝓕 q✝
x✝ : Locally p✝ 𝓕 X P ∧ Locally q✝ 𝓕 X P
hpX✝ : Locally p✝ 𝓕 X P
hqX✝ : Locally q✝ 𝓕 X P
n : ℕ
p q : (ι → Ω → E) → Prop
hp : IsStable 𝓕 p
hq : IsStable 𝓕 q
hpX : Locally p 𝓕 X P
hqX : Locally q 𝓕 X P
i : ι
ω : Ω
⊢ stoppedProcess
      (fun i ↦ {ω | ⊥ < hpX.localSeq n ω ∧ ⊥ < hqX.localSeq n ω}.indicator (stoppedProcess X (hpX.localSeq n) i))
      (hqX.localSeq n) i ω =
    {ω | ⊥ < hqX.localSeq n ω}.indicator
      ({ω | ⊥ < hpX.localSeq n ω}.indicator (stoppedProcess (stoppedProcess X (hpX.localSeq n)) (hqX.localSeq n) i)) ω
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
t : ℝ
⊢ Integrable (fun ω ↦ rexp (t * (X ω + Y ω))) (⇑κ ∘ₘ ν)

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : CommSemiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
σ : Subrepresentation ρ
c : A[G]
v : ρ.asModule
hv : v ∈ σ.toSubmodule.carrier
⊢ c • v ∈ σ.toSubmodule.carrier

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
inst✝³ : CommSemiring A
inst✝² : Monoid G
inst✝¹ : AddCommMonoid W
inst✝ : Module A W
ρ : Representation A G W
σ : Subrepresentation ρ
v : W
⊢ v ∈ σ.asSubmodule ↔ v ∈ σ

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : CommSemiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
σ : Subrepresentation (Representation.ofModule M)
m : M
hm : m ∈ σ.toSubmodule.carrier
g : G
a : A
⊢ MonoidAlgebra.single g 1 • m ∈ σ.toSubmodule.carrier

Tactic:
by

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

Goal state before:
pp: ι : Type u_1
Ω : Type u_2
E : Type u_3
mΩ : MeasurableSpace Ω
P : Measure Ω
inst✝⁴ : LinearOrder ι
𝓕 : Filtration ι mΩ
X : ι → Ω → E
p q : (ι → Ω → E) → Prop
inst✝³ : OrderBot ι
inst✝² : Zero E
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
hp : IsStable 𝓕 p
hq : IsStable 𝓕 q
⊢ Locally (fun Y ↦ p Y ∧ q Y) 𝓕 X P ↔ Locally p 𝓕 X P ∧ Locally q 𝓕 X P

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: case single
A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : CommSemiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
σ : Subrepresentation (Representation.ofModule M)
m : M
hm : m ∈ σ.toSubmodule.carrier
g : G
a : A
⊢ (algebraMap A A[G]) a • MonoidAlgebra.single g 1 • m ∈ σ.toSubmodule.carrier

Tactic:
exact σ.toSubmodule.smul_mem' ((algebraMap A A) a) <| by
        simpa [Representation.ofModule, RestrictScalars.lsmul] using! σ.apply_mem_toSubmodule g hm

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : CommSemiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
σ : Subrepresentation (Representation.ofModule M)
c : A[G]
m : M
hm : m ∈ σ.toSubmodule.carrier
⊢ c • m ∈ σ.toSubmodule.carrier

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
M : Type u_4
inst✝³ : CommSemiring A
inst✝² : Monoid G
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
σ : Subrepresentation (Representation.ofModule M)
m : M
⊢ m ∈ σ.asSubmodule' ↔ m ∈ σ

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : CommSemiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
N : Submodule A[G] M
g : G
v : RestrictScalars A A[G] M
hv : v ∈ { toAddSubmonoid := N.toAddSubmonoid, smul_mem' := ⋯ }
⊢ ((Representation.ofModule M) g) v ∈ { toAddSubmonoid := N.toAddSubmonoid, smul_mem' := ⋯ }

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
M : Type u_4
inst✝³ : CommSemiring A
inst✝² : Monoid G
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
N : Submodule A[G] M
m : M
⊢ m ∈ ofSubmodule N ↔ m ∈ N

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : CommSemiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
N : Submodule A[G] ρ.asModule
a : A
w : W
hw : w ∈ N.carrier
⊢ a • w ∈ N.carrier

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : CommSemiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
N : Submodule A[G] ρ.asModule
g : G
w : W
hw : w ∈ { toAddSubmonoid := N.toAddSubmonoid, smul_mem' := ⋯ }
⊢ (ρ g) w ∈ { toAddSubmonoid := N.toAddSubmonoid, smul_mem' := ⋯ }

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : CommSemiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
⊢ ∀ {a b : Subrepresentation ρ},
    { toFun := asSubmodule, invFun := ofSubmodule', left_inv := ⋯, right_inv := ⋯ } a ≤
        { toFun := asSubmodule, invFun := ofSubmodule', left_inv := ⋯, right_inv := ⋯ } b ↔
      a ≤ b

Tactic:
by

Goal state after:
Module: Mathlib.RepresentationTheory.Subrepresentation

Goal state before:
pp: A : Type u_1
G : Type u_2
W : Type u_3
M : Type u_4
inst✝⁵ : CommSemiring A
inst✝⁴ : Monoid G
inst✝³ : AddCommMonoid W
inst✝² : Module A W
ρ : Representation A G W
inst✝¹ : AddCommMonoid M
inst✝ : Module A[G] M
⊢ ∀ {a b : Submodule A[G] M},
    { toFun := ofSubmodule, invFun := asSubmodule', left_inv := ⋯, right_inv := ⋯ } a ≤
        { toFun := ofSubmodule, invFun := asSubmodule', left_inv := ⋯, right_inv := ⋯ } b ↔
      a ≤ b

Tactic:
by

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

Goal state before:
pp: ι : Type u_1
Ω : Type u_2
mΩ : MeasurableSpace Ω
P : Measure Ω
inst✝⁶ : ConditionallyCompleteLinearOrderBot ι
inst✝⁵ : TopologicalSpace ι
inst✝⁴ : OrderTopology ι
𝓕 : Filtration ι mΩ
inst✝³ : DenselyOrdered ι
inst✝² : FirstCountableTopology ι
inst✝¹ : NoMaxOrder ι
τ : ℕ → Ω → WithTop ι
inst✝ : 𝓕.IsRightContinuous
hτ : IsPreLocalizingSequence 𝓕 τ P
⊢ ∀ᵐ (ω : Ω) ∂P, Tendsto (fun x ↦ ⨅ j, ⨅ (_ : j ≥ x), τ j ω) atTop (𝓝 ⊤)

Tactic:
by

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

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
⊢ 0 < ↑p

Tactic:
by

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
⊢ 0 < ↑q

Tactic:
by

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

Goal state before:
pp: ι : Type u_1
Ω : Type u_2
E : Type u_3
mΩ : MeasurableSpace Ω
P : Measure Ω
inst✝⁷ : ConditionallyCompleteLinearOrderBot ι
inst✝⁶ : TopologicalSpace ι
inst✝⁵ : OrderTopology ι
𝓕 : Filtration ι mΩ
X : ι → Ω → E
p : (ι → Ω → E) → Prop
inst✝⁴ : Zero E
inst✝³ : DenselyOrdered ι
inst✝² : FirstCountableTopology ι
inst✝¹ : NoMaxOrder ι
τ : ℕ → Ω → WithTop ι
hp : IsStable 𝓕 p
inst✝ : 𝓕.IsRightContinuous
hτ : IsPreLocalizingSequence 𝓕 τ P
hpτ : ∀ (n : ℕ), p (stoppedProcess (fun i ↦ {ω | ⊥ < τ n ω}.indicator (X i)) (τ n))
⊢ Locally p 𝓕 X P

Tactic:
by

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

Goal state before:
pp: ι : Type u_1
Ω : Type u_2
mΩ : MeasurableSpace Ω
P : Measure Ω
inst✝⁴ : ConditionallyCompleteLinearOrderBot ι
inst✝³ : TopologicalSpace ι
inst✝² : OrderTopology ι
𝓕 : Filtration ι mΩ
inst✝¹ : SecondCountableTopology ι
inst✝ : IsFiniteMeasure P
τ : ℕ → Ω → WithTop ι
σ : ℕ → ℕ → Ω → WithTop ι
hτ : IsLocalizingSequence 𝓕 τ P
hσ : ∀ (n : ℕ), IsLocalizingSequence 𝓕 (σ n) P
T : ℕ → ι
hT : Tendsto T atTop atTop
n : ℕ
hn : ∀ (k : ℕ), (1 / 2) ^ n < P {ω | σ n k ω < min (τ n ω) ↑(T n)}
this : (1 / 2) ^ n ≤ P (⋂ k, {ω | σ n k ω < min (τ n ω) ↑(T n)})
⊢ ¬(1 / 2) ^ n ≤ 0

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ : Measure α
f : α → ℝ
hf : AEStronglyMeasurable f μ
A : ℝ
⊢ AEStronglyMeasurable (ProbabilityTheory.truncation f A) μ

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: α : Type u_1
f : α → ℝ
A : ℝ
x : α
⊢ |truncation f A x| ≤ |A|

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: α : Type u_1
f : α → ℝ
⊢ truncation f 0 = 0

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: α : Type u_1
f : α → ℝ
A : ℝ
x : α
⊢ |truncation f A x| ≤ |f x|

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: α : Type u_1
f : α → ℝ
A : ℝ
x : α
h : |f x| < A
⊢ truncation f A x = f x

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: α : Type u_1
f : α → ℝ
A : ℝ
h : ∀ (x : α), 0 ≤ f x
x : α
hx : 0 < f x
h'x : f x ≤ A
⊢ -A < f x

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: case inr
α : Type u_1
f : α → ℝ
A : ℝ
h : ∀ (x : α), 0 ≤ f x
x : α
hx : 0 = f x
⊢ truncation f A x = ((Set.Ioc 0 A).indicator id ∘ f) x

Tactic:
simp only [truncation, indicator, hx, id, Function.comp_apply, ite_self]

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: α : Type u_1
f : α → ℝ
A : ℝ
h : ∀ (x : α), 0 ≤ f x
⊢ truncation f A = (Set.Ioc 0 A).indicator id ∘ f

Tactic:
by

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ : Measure α
f : α → ℝ
inst✝ : IsFiniteMeasure μ
hf : AEStronglyMeasurable f μ
A : ℝ
⊢ Integrable (truncation f A) μ

Tactic:
by

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
⊢ ∫ (x : Ω), (fun ω ↦ rexp (t * (X ω + Y ω))) x ∂κ ω' ≤
    (∫ (x : Ω), (fun ω ↦ rexp (t * X ω) ^ ↑p) x ∂κ ω') ^ (1 / ↑p) *
      (∫ (x : Ω), (fun ω ↦ rexp (t * Y ω) ^ ↑q) x ∂κ ω') ^ (1 / ↑q)

Tactic:
by

Goal state after: