mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.ProbabilityMassFunction.Constructions

Goal state before:
pp: α : Type u_1
β : Type u_2
inst✝¹ : Fintype α
inst✝ : Fintype β
f : α → ℝ≥0∞
h : ∑ a, f a = 1
g : α → β
b : β
⊢ (∑' (a : α), if b = g a then f a else 0) = ∑ a, if b = g a then f a else 0

Tactic:
exact tsum_eq_sum fun _ h ↦ (h <| mem_univ _).elim

Goal state after:
Module: Mathlib.Probability.Distributions.Uniform

Goal state before:
pp: case neg.right
Ω : Type u_2
x✝ : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → ℝ
s : Set ℝ
hcs : IsCompact s
huX : IsUniform X s ℙ volume
hnt : ¬volume s = 0 ∧ ¬volume s = ∞
this✝ : IsProbabilityMeasure ℙ
ind : ℝ → ℝ≥0∞ := (volume s)⁻¹ • 1
this : ∀ (x : ℝ), ‖x‖ₑ * s.indicator ind x = s.indicator (fun x ↦ ‖x‖ₑ * ind x) x
⊢ ∫⁻ (x : ℝ), ‖x‖ₑ * s.indicator ind x ≠ ∞

Tactic:
simp only [ind, this, lintegral_indicator hcs.measurableSet, mul_one, smul_eq_mul,
    Pi.one_apply, Pi.smul_apply]

Goal state after:
case neg.right
Ω : Type u_2
x✝ : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → ℝ
s : Set ℝ
hcs : IsCompact s
huX : IsUniform X s ℙ volume
hnt : ¬volume s = 0 ∧ ¬volume s = ∞
this✝ : IsProbabilityMeasure ℙ
ind : ℝ → ℝ≥0∞ := (volume s)⁻¹ • 1
this : ∀ (x : ℝ), ‖x‖ₑ * s.indicator ind x = s.indicator (fun x ↦ ‖x‖ₑ * ind x) x
⊢ ∫⁻ (x : ℝ) in s, ‖x‖ₑ * (volume s)⁻¹ ∂volume ≠ ∞
Module: Mathlib.Probability.Independence.InfinitePi

Goal state before:
pp: ι : Type u_1
Ω : Type u_2
mΩ : MeasurableSpace Ω
P : Measure Ω
𝓧 : ι → Type u_3
m𝓧 : (i : ι) → MeasurableSpace (𝓧 i)
X : (i : ι) → Ω → 𝓧 i
μ : (i : ι) → Measure (𝓧 i)
hX : ∀ (i : ι), HasLaw (X i) (μ i) P
h1 : iIndepFun X P
h2 : AEMeasurable (fun ω i ↦ X i ω) P
⊢ map (fun ω i ↦ X i ω) P = infinitePi μ

Tactic:
have := h1.isProbabilityMeasure
    rw [(iIndepFun_iff_map_fun_eq_infinitePi_map₀ h2).1 h1]
    simp_rw [fun i ↦ (hX i).map_eq]

Goal state after:
Module: Mathlib.Probability.Distributions.Uniform

Goal state before:
pp: α : Type u_1
s : Multiset α
hs : s ≠ 0
a : α
ha : a ∉ s.toFinset
⊢ Multiset.count a s = 0

Tactic:
by rwa [Multiset.count_eq_zero, ← Multiset.mem_toFinset]

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

Goal state before:
pp: ι : Type u_1
Ω : ι → Type u_4
mΩ : (i : ι) → MeasurableSpace (Ω i)
P : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (P i)
i j : ι
hij : i ≠ j
⊢ (map (fun ω ↦ ω i) (infinitePi P)).prod (map (fun ω ↦ ω j) (infinitePi P)) = (P i).prod (P j)

pp: case hf
ι : Type u_1
Ω : ι → Type u_4
mΩ : (i : ι) → MeasurableSpace (Ω i)
P : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (P i)
i j : ι
hij : i ≠ j
⊢ AEMeasurable (fun ω ↦ ω i) (infinitePi P)

pp: case hg
ι : Type u_1
Ω : ι → Type u_4
mΩ : (i : ι) → MeasurableSpace (Ω i)
P : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (P i)
i j : ι
hij : i ≠ j
⊢ AEMeasurable (fun ω ↦ ω j) (infinitePi P)

pp: case a
ι : Type u_1
Ω : ι → Type u_4
mΩ : (i : ι) → MeasurableSpace (Ω i)
P : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (P i)
i j : ι
hij : i ≠ j
⊢ (fun ω ↦ ω i) ⟂ᵢ[infinitePi P] fun ω ↦ ω j

Tactic:
rotate_right

Goal state after:
case a
ι : Type u_1
Ω : ι → Type u_4
mΩ : (i : ι) → MeasurableSpace (Ω i)
P : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (P i)
i j : ι
hij : i ≠ j
⊢ (fun ω ↦ ω i) ⟂ᵢ[infinitePi P] fun ω ↦ ω j

ι : Type u_1
Ω : ι → Type u_4
mΩ : (i : ι) → MeasurableSpace (Ω i)
P : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (P i)
i j : ι
hij : i ≠ j
⊢ (map (fun ω ↦ ω i) (infinitePi P)).prod (map (fun ω ↦ ω j) (infinitePi P)) = (P i).prod (P j)

case hf
ι : Type u_1
Ω : ι → Type u_4
mΩ : (i : ι) → MeasurableSpace (Ω i)
P : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (P i)
i j : ι
hij : i ≠ j
⊢ AEMeasurable (fun ω ↦ ω i) (infinitePi P)

case hg
ι : Type u_1
Ω : ι → Type u_4
mΩ : (i : ι) → MeasurableSpace (Ω i)
P : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (P i)
i j : ι
hij : i ≠ j
⊢ AEMeasurable (fun ω ↦ ω j) (infinitePi P)
Module: Mathlib.Probability.Kernel.Condexp

Goal state before:
pp: Ω : Type u_1
F : Type u_2
m mΩ : MeasurableSpace Ω
inst✝⁴ : StandardBorelSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
inst✝² : NormedAddCommGroup F
f : Ω → F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hf_int : Integrable f μ
⊢ μ[f | m ⊓ mΩ] =ᵐ[μ] fun ω ↦ ∫ (y : Ω), f y ∂(condExpKernel μ m) ω

Tactic:
rcases isEmpty_or_nonempty Ω with h | h
  · have : μ = 0 := Measure.eq_zero_of_isEmpty μ
    simpa [this] using! trivial
  have hX : @Measurable Ω Ω mΩ (m ⊓ mΩ) id := measurable_id.mono le_rfl (inf_le_right : m ⊓ mΩ ≤ mΩ)
  simp_rw [condExpKernel_apply_eq_condDistrib]
  have h := condExp_ae_eq_integral_condDistrib_id hX hf_int
  simpa only [MeasurableSpace.comap_id, id_eq] using! h

Goal state after:
Module: Mathlib.Probability.Kernel.Condexp

Goal state before:
pp: case refine_1
Ω : Type u_1
F : Type u_2
m mΩ : MeasurableSpace Ω
inst✝⁴ : StandardBorelSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
inst✝² : NormedAddCommGroup F
f : Ω → F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hm : m ≤ mΩ
hf_int : Integrable f μ
⊢ Integrable (AEStronglyMeasurable.mk f ⋯) μ

pp: case refine_2
Ω : Type u_1
F : Type u_2
m mΩ : MeasurableSpace Ω
inst✝⁴ : StandardBorelSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
inst✝² : NormedAddCommGroup F
f : Ω → F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hm : m ≤ mΩ
hf_int : Integrable f μ
⊢ (fun ω ↦ ∫ (y : Ω), AEStronglyMeasurable.mk f ⋯ y ∂(condExpKernel μ m) ω) =ᵐ[μ.trim hm] fun ω ↦
    ∫ (y : Ω), f y ∂(condExpKernel μ m) ω

Tactic:
· rwa [integrable_congr hf_int.1.ae_eq_mk.symm]

Goal state after:
case refine_2
Ω : Type u_1
F : Type u_2
m mΩ : MeasurableSpace Ω
inst✝⁴ : StandardBorelSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
inst✝² : NormedAddCommGroup F
f : Ω → F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hm : m ≤ mΩ
hf_int : Integrable f μ
⊢ (fun ω ↦ ∫ (y : Ω), AEStronglyMeasurable.mk f ⋯ y ∂(condExpKernel μ m) ω) =ᵐ[μ.trim hm] fun ω ↦
    ∫ (y : Ω), f y ∂(condExpKernel μ m) ω
Module: Mathlib.Probability.Independence.ZeroOne

Goal state before:
pp: case pos
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m0 : MeasurableSpace Ω
κ : Kernel α Ω
μα : Measure α
t : Set Ω
h_indep : ∀ᵐ (a : α) ∂μα, (κ a) (t ∩ t) = (κ a) t * (κ a) t
a : α
ha : (κ a) (t ∩ t) = (κ a) t * (κ a) t
h0 : ¬(κ a) t = 0
h_top : (κ a) t = ∞
⊢ (κ a) t = 0 ∨ (κ a) t = 1 ∨ (κ a) t = ∞

pp: case neg
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m0 : MeasurableSpace Ω
κ : Kernel α Ω
μα : Measure α
t : Set Ω
h_indep : ∀ᵐ (a : α) ∂μα, (κ a) (t ∩ t) = (κ a) t * (κ a) t
a : α
ha : (κ a) (t ∩ t) = (κ a) t * (κ a) t
h0 : ¬(κ a) t = 0
h_top : ¬(κ a) t = ∞
⊢ (κ a) t = 0 ∨ (κ a) t = 1 ∨ (κ a) t = ∞

Tactic:
· exact Or.inr (Or.inr h_top)

Goal state after:
case neg
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m0 : MeasurableSpace Ω
κ : Kernel α Ω
μα : Measure α
t : Set Ω
h_indep : ∀ᵐ (a : α) ∂μα, (κ a) (t ∩ t) = (κ a) t * (κ a) t
a : α
ha : (κ a) (t ∩ t) = (κ a) t * (κ a) t
h0 : ¬(κ a) t = 0
h_top : ¬(κ a) t = ∞
⊢ (κ a) t = 0 ∨ (κ a) t = 1 ∨ (κ a) t = ∞
Module: Mathlib.Probability.Kernel.Category.Stoch

Goal state before:
pp: X✝ Y✝ : Stoch
κ✝ : X✝ ⟶ Y✝
X Y : Stoch
κ : Kernel X.obj.carrier Y.obj.carrier
inst✝¹ : IsDeterministic κ
inst✝ : IsMarkovKernel κ
⊢ { hom := { hom := κ, property := ⋯ }, property := ⋯ } ≫ Δ =
    Δ ≫ ({ hom := { hom := κ, property := ⋯ }, property := ⋯ } ⊗ₘ { hom := { hom := κ, property := ⋯ }, property := ⋯ })

Tactic:
by
    ext : 1; dsimp
    exact Deterministic.copy_natural _

Goal state after:
Module: Mathlib.Probability.Kernel.Category.SFinKer

Goal state before:
pp: X Y : SFinKer
⊢ Kernel.deterministic id ⋯ ∥ₖ (Kernel.deterministic id ⋯).map Prod.snd ∘ₖ Kernel.deterministic ⇑prodAssoc ⋯ =
    (Kernel.deterministic id ⋯).map Prod.fst ∥ₖ Kernel.deterministic id ⋯

Tactic:
Kernel.deterministic_map (by fun_prop) (by fun_prop)

Goal state after:
X Y : SFinKer
⊢ Kernel.deterministic id ⋯ ∥ₖ Kernel.deterministic (Prod.snd ∘ id) ⋯ ∘ₖ Kernel.deterministic ⇑prodAssoc ⋯ =
    (Kernel.deterministic id ⋯).map Prod.fst ∥ₖ Kernel.deterministic id ⋯
Module: Mathlib.Probability.Kernel.Category.SFinKer

Goal state before:
pp: X Y : SFinKer
⊢ Kernel.deterministic id ⋯ ∥ₖ Kernel.deterministic (Prod.snd ∘ id) ⋯ ∘ₖ Kernel.deterministic ⇑prodAssoc ⋯ =
    (Kernel.deterministic id ⋯).map Prod.fst ∥ₖ Kernel.deterministic id ⋯

Tactic:
Kernel.deterministic_map (by fun_prop) (by fun_prop)

Goal state after:
X Y : SFinKer
⊢ Kernel.deterministic id ⋯ ∥ₖ Kernel.deterministic (Prod.snd ∘ id) ⋯ ∘ₖ Kernel.deterministic ⇑prodAssoc ⋯ =
    Kernel.deterministic (Prod.fst ∘ id) ⋯ ∥ₖ Kernel.deterministic id ⋯
Module: Mathlib.Probability.Kernel.Category.SFinKer

Goal state before:
pp: X Y : SFinKer
⊢ Kernel.deterministic id ⋯ ∥ₖ Kernel.deterministic (Prod.snd ∘ id) ⋯ ∘ₖ Kernel.deterministic ⇑prodAssoc ⋯ =
    Kernel.deterministic (Prod.fst ∘ id) ⋯ ∥ₖ Kernel.deterministic id ⋯

Tactic:
Kernel.deterministic_map (by fun_prop) (by fun_prop)

Goal state after:
X Y : SFinKer
⊢ Kernel.deterministic id ⋯ ∥ₖ Kernel.deterministic (Prod.snd ∘ id) ⋯ ∘ₖ Kernel.deterministic ⇑prodAssoc ⋯ =
    Kernel.deterministic (Prod.fst ∘ id) ⋯ ∥ₖ Kernel.deterministic id ⋯
Module: Mathlib.Probability.Independence.BoundedContinuousFunction

Goal state before:
pp: Ω : Type u_1
S : Type u_2
mΩ : MeasurableSpace Ω
P : Measure Ω
E : S → Type u_4
inst✝⁵ : (s : S) → TopologicalSpace (E s)
inst✝⁴ : (s : S) → MeasurableSpace (E s)
inst✝³ : ∀ (s : S), BorelSpace (E s)
inst✝² : ∀ (s : S), HasOuterApproxClosed (E s)
X : (s : S) → Ω → E s
inst✝¹ : Fintype S
inst✝ : IsProbabilityMeasure P
A : Set Ω
mA : NullMeasurableSet A P
mX : ∀ (s : S), AEMeasurable (X s) P
h : ∀ (f : (s : S) → E s →ᵇ ℝ), ∫ (ω : Ω) in A, ∏ s, (f s) (X s ω) ∂P = P.real A * ∫ (ω : Ω), ∏ s, (f s) (X s ω) ∂P
f : ℝ →ᵇ ℝ
g : (t : S) → E t →ᵇ ℝ
h1 :
  ∀ (ω : Ω),
    f (A.indicator 1 ω) * ∏ s, (g s) (X s ω) =
      A.indicator (fun ω ↦ f 1 * ∏ s, (g s) (X s ω)) ω + f 0 * ∏ s, (g s) (X s ω) -
        A.indicator (fun ω ↦ f 0 * ∏ s, (g s) (X s ω)) ω
h2 : ∀ (ω : Ω), f (A.indicator 1 ω) = A.indicator (fun x ↦ f 1) ω + Aᶜ.indicator (fun x ↦ f 0) ω
hg : ∀ {c : ℝ}, Integrable (fun ω ↦ c * ∏ s, (g s) (X s ω)) P
⊢ ∫ (x : Ω), f (A.indicator 1 x) * ∏ x_1, (g x_1) (X x_1 x) ∂P =
    (∫ (x : Ω), f (A.indicator 1 x) ∂P) * ∫ (x : Ω), ∏ x_1, (g x_1) (X x_1 x) ∂P

Tactic:
h1,

Goal state after:
Ω : Type u_1
S : Type u_2
mΩ : MeasurableSpace Ω
P : Measure Ω
E : S → Type u_4
inst✝⁵ : (s : S) → TopologicalSpace (E s)
inst✝⁴ : (s : S) → MeasurableSpace (E s)
inst✝³ : ∀ (s : S), BorelSpace (E s)
inst✝² : ∀ (s : S), HasOuterApproxClosed (E s)
X : (s : S) → Ω → E s
inst✝¹ : Fintype S
inst✝ : IsProbabilityMeasure P
A : Set Ω
mA : NullMeasurableSet A P
mX : ∀ (s : S), AEMeasurable (X s) P
h : ∀ (f : (s : S) → E s →ᵇ ℝ), ∫ (ω : Ω) in A, ∏ s, (f s) (X s ω) ∂P = P.real A * ∫ (ω : Ω), ∏ s, (f s) (X s ω) ∂P
f : ℝ →ᵇ ℝ
g : (t : S) → E t →ᵇ ℝ
h1 :
  ∀ (ω : Ω),
    f (A.indicator 1 ω) * ∏ s, (g s) (X s ω) =
      A.indicator (fun ω ↦ f 1 * ∏ s, (g s) (X s ω)) ω + f 0 * ∏ s, (g s) (X s ω) -
        A.indicator (fun ω ↦ f 0 * ∏ s, (g s) (X s ω)) ω
h2 : ∀ (ω : Ω), f (A.indicator 1 ω) = A.indicator (fun x ↦ f 1) ω + Aᶜ.indicator (fun x ↦ f 0) ω
hg : ∀ {c : ℝ}, Integrable (fun ω ↦ c * ∏ s, (g s) (X s ω)) P
⊢ ∫ (x : Ω),
      A.indicator (fun ω ↦ f 1 * ∏ s, (g s) (X s ω)) x + f 0 * ∏ x_1, (g x_1) (X x_1 x) -
        A.indicator (fun ω ↦ f 0 * ∏ s, (g s) (X s ω)) x ∂P =
    (∫ (x : Ω), f (A.indicator 1 x) ∂P) * ∫ (x : Ω), ∏ x_1, (g x_1) (X x_1 x) ∂P
Module: Mathlib.Probability.Moments.Tilted

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
t : ℝ
s : Set Ω
hs : MeasurableSet s
ht : Integrable (fun ω ↦ rexp (t * X ω)) μ
⊢ (μ.tilted fun x ↦ t * X x) s = ∫⁻ (a : Ω) in s, ENNReal.ofReal (rexp (t * X a - cgf X μ t)) ∂μ

Tactic:
by
  rcases eq_zero_or_neZero μ with rfl | hμ
  · simp
  · simp_rw [tilted_mul_apply_mgf' hs, exp_sub, exp_cgf ht]

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)
⊢ 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)

Tactic:
h1,

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)
⊢ Measure.map (fun a ↦ (k a, g a, f a)) μ =
    Measure.map (⇑e.symm) (Measure.map (⇑e) (Measure.map (fun a ↦ (k a, g a, f a)) 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
h : HasSubgaussianMGF X c κ ν
p : ℝ≥0
ω' : Ω'
hi : ∀ (t : ℝ), Integrable (fun ω ↦ rexp (t * X ω)) (κ ω')
t : ℝ
hp : ¬p = 0
hf : ∫⁻ (x : Ω), ENNReal.ofReal (rexp (↑p * t * X x)) ∂κ ω' < ∞
ω : Ω
⊢ ENNReal.ofReal (rexp (t * X ω)) ^ ↑p = ENNReal.ofReal (rexp (↑p * t * X ω))

Tactic:
ENNReal.ofReal_rpow_of_nonneg (by positivity),

Goal state after:
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
p : ℝ≥0
ω' : Ω'
hi : ∀ (t : ℝ), Integrable (fun ω ↦ rexp (t * X ω)) (κ ω')
t : ℝ
hp : ¬p = 0
hf : ∫⁻ (x : Ω), ENNReal.ofReal (rexp (↑p * t * X x)) ∂κ ω' < ∞
ω : Ω
⊢ ENNReal.ofReal (rexp (t * X ω) ^ ↑p) = ENNReal.ofReal (rexp (↑p * t * X ω))

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
p : ℝ≥0
ω' : Ω'
hi : ∀ (t : ℝ), Integrable (fun ω ↦ rexp (t * X ω)) (κ ω')
t : ℝ
hp : ¬p = 0
hf : ∫⁻ (x : Ω), ENNReal.ofReal (rexp (↑p * t * X x)) ∂κ ω' < ∞
ω : Ω
⊢ 0 ≤ ↑p
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)
h2 :
  ⇑(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)
h2_symm :
  ⇑(Kernel.id ×ₖ (condDistrib g k μ ×ₖ condDistrib f k μ)) ∘ₘ Measure.map k μ =
    Measure.map (⇑e.symm) (⇑(Kernel.id ×ₖ condDistrib g k μ ×ₖ condDistrib f k μ) ∘ₘ Measure.map k μ)
⊢ Measure.map (fun ω ↦ (k ω, g ω, f ω)) μ =
      ⇑(Kernel.id ×ₖ (condDistrib g k μ ×ₖ condDistrib f k μ)) ∘ₘ Measure.map k μ ↔
    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

Tactic:
h1,

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)
h2 :
  ⇑(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)
h2_symm :
  ⇑(Kernel.id ×ₖ (condDistrib g k μ ×ₖ condDistrib f k μ)) ∘ₘ Measure.map k μ =
    Measure.map (⇑e.symm) (⇑(Kernel.id ×ₖ condDistrib g k μ ×ₖ condDistrib f k μ) ∘ₘ Measure.map k μ)
⊢ Measure.map (fun ω ↦ (k ω, g ω, f ω)) μ =
      ⇑(Kernel.id ×ₖ (condDistrib g k μ ×ₖ condDistrib f k μ)) ∘ₘ Measure.map k μ ↔
    Measure.map (⇑e) (Measure.map (fun a ↦ (k a, g a, f a)) μ) =
      ⇑(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
h : HasSubgaussianMGF X c κ ν
t : ℝ
p : ℝ≥0
hp0 : ¬p = 0
h' : ∫⁻ (a : Ω), ‖rexp (↑p * t * X a)‖ₑ ∂⇑κ ∘ₘ ν < ∞
ω : Ω
⊢ ENNReal.ofReal (rexp (t * X ω)) ^ ↑p = ENNReal.ofReal (rexp (↑p * t * X ω))

Tactic:
ENNReal.ofReal_rpow_of_nonneg (by positivity),

Goal state after:
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
t : ℝ
p : ℝ≥0
hp0 : ¬p = 0
h' : ∫⁻ (a : Ω), ‖rexp (↑p * t * X a)‖ₑ ∂⇑κ ∘ₘ ν < ∞
ω : Ω
⊢ ENNReal.ofReal (rexp (t * X ω) ^ ↑p) = ENNReal.ofReal (rexp (↑p * t * X ω))

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
t : ℝ
p : ℝ≥0
hp0 : ¬p = 0
h' : ∫⁻ (a : Ω), ‖rexp (↑p * t * X a)‖ₑ ∂⇑κ ∘ₘ ν < ∞
ω : Ω
⊢ 0 ≤ ↑p
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 ext; simp

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 ext; simp

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: case neg
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
⊢ (if -A < f x ∧ f x ≤ A then f x else 0) = if True ∧ f x ≤ A then f x else 0

Tactic:
· simp only [h'x, and_false]

Goal state after:
Module: Mathlib.RepresentationTheory.Action

Goal state before:
pp: k : Type u
G : Type v
V : Type u'
W : Type v'
inst✝⁵ : Monoid G
inst✝⁴ : Semiring k
inst✝³ : AddCommGroup V
inst✝² : Module k V
inst✝¹ : AddCommGroup W
inst✝ : Module k W
σ : Representation k G V
ρ : Representation k G W
X Y Z : Action (Type w) G
⊢ MonoidAlgebra.mapDomainLinearMap k k ⇑(ConcreteCategory.hom (X.ρ 1)) = 1

Tactic:
by ext; simp

Goal state after:
Module: Mathlib.RepresentationTheory.Action

Goal state before:
pp: k : Type u
G : Type v
V : Type u'
W : Type v'
inst✝⁵ : Monoid G
inst✝⁴ : Semiring k
inst✝³ : AddCommGroup V
inst✝² : Module k V
inst✝¹ : AddCommGroup W
inst✝ : Module k W
σ : Representation k G V
ρ : Representation k G W
X Y Z : Action (Type w) G
x✝¹ x✝ : G
⊢ MonoidAlgebra.mapDomainLinearMap k k ⇑(ConcreteCategory.hom (X.ρ (x✝¹ * x✝))) =
    MonoidAlgebra.mapDomainLinearMap k k ⇑(ConcreteCategory.hom (X.ρ x✝¹)) *
      MonoidAlgebra.mapDomainLinearMap k k ⇑(ConcreteCategory.hom (X.ρ x✝))

Tactic:
by ext; simp

Goal state after:
Module: Mathlib.RepresentationTheory.Action

Goal state before:
pp: k : Type u
G : Type v
inst✝¹ : Monoid G
inst✝ : Semiring k
⊢ (ε k G).comp (η k G) = IntertwiningMap.id (linearize k G (𝟙_ (Action (Type u) G)))

Tactic:
by ext; simp

Goal state after:
Module: Mathlib.RepresentationTheory.Action

Goal state before:
pp: k : Type u
G : Type v
inst✝¹ : Monoid G
inst✝ : Semiring k
⊢ (η k G).comp (ε k G) = IntertwiningMap.id (trivial k G k)

Tactic:
by ext; simp

Goal state after:
Module: Mathlib.RepresentationTheory.Equiv

Goal state before:
pp: k : Type u
inst✝⁸ : Semiring k
G : Type v
inst✝⁷ : Monoid G
V : Type v'
inst✝⁶ : AddCommMonoid V
inst✝⁵ : Module k V
W : Type w'
inst✝⁴ : AddCommMonoid W
inst✝³ : Module k W
H : Type w
inst✝² : Subsingleton H
inst✝¹ : MulOneClass H
inst✝ : MulAction G H
g : G
⊢ ↑(MonoidAlgebra.mapDomainLinearEquiv k k (Equiv.funUnique (Fin 1) G)) ∘ₗ (diagonal k G 1) g =
    (leftRegular k G) g ∘ₗ ↑(MonoidAlgebra.mapDomainLinearEquiv k k (Equiv.funUnique (Fin 1) G))

Tactic:
by ext; simp

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'
f : α → V
g : G
⊢ ((linearCombination k fun x ↦ (σ x.2) (f x.1)) ∘ₗ
        ↑(curryLinearEquiv k).symm ∘ₗ mapRange.linearMap ↑(MonoidAlgebra.coeffLinearEquiv k)) ∘ₗ
      (free k G α) g =
    σ g ∘ₗ
      (linearCombination k fun x ↦ (σ x.2) (f x.1)) ∘ₗ
        ↑(curryLinearEquiv k).symm ∘ₗ mapRange.linearMap ↑(MonoidAlgebra.coeffLinearEquiv k)

Tactic:
by ext; simp

Goal state after: