mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Independence.InfinitePi

Goal state before:
pp: case hg
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
mX : AEMeasurable (fun ω i ↦ X i ω) P
h : ∀ (s : Finset ι), iIndepFun (s.restrict X) P
this✝ : IsProbabilityMeasure P
x✝ : ∀ (i : ι), IsProbabilityMeasure (map (fun x ↦ X i x) P)
s : Finset ι
t : (i : ι) → Set (𝓧 i)
ht : ∀ (i : ι), MeasurableSet (t i)
this : (↑s).pi t = s.restrict ⁻¹' Set.univ.pi fun i ↦ t ↑i
⊢ AEMeasurable s.restrict (map (fun ω i ↦ X i ω) P)

pp: case hf
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
mX : AEMeasurable (fun ω i ↦ X i ω) P
h : ∀ (s : Finset ι), iIndepFun (s.restrict X) P
this✝ : IsProbabilityMeasure P
x✝ : ∀ (i : ι), IsProbabilityMeasure (map (fun x ↦ X i x) P)
s : Finset ι
t : (i : ι) → Set (𝓧 i)
ht : ∀ (i : ι), MeasurableSet (t i)
this : (↑s).pi t = s.restrict ⁻¹' Set.univ.pi fun i ↦ t ↑i
⊢ AEMeasurable (fun ω i ↦ X i ω) P

pp: case hf
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
mX : AEMeasurable (fun ω i ↦ X i ω) P
h : ∀ (s : Finset ι), iIndepFun (s.restrict X) P
this✝ : IsProbabilityMeasure P
x✝ : ∀ (i : ι), IsProbabilityMeasure (map (fun x ↦ X i x) P)
s : Finset ι
t : (i : ι) → Set (𝓧 i)
ht : ∀ (i : ι), MeasurableSet (t i)
this : (↑s).pi t = s.restrict ⁻¹' Set.univ.pi fun i ↦ t ↑i
⊢ Measurable s.restrict

pp: case hs
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
mX : AEMeasurable (fun ω i ↦ X i ω) P
h : ∀ (s : Finset ι), iIndepFun (s.restrict X) P
this✝ : IsProbabilityMeasure P
x✝ : ∀ (i : ι), IsProbabilityMeasure (map (fun x ↦ X i x) P)
s : Finset ι
t : (i : ι) → Set (𝓧 i)
ht : ∀ (i : ι), MeasurableSet (t i)
this : (↑s).pi t = s.restrict ⁻¹' Set.univ.pi fun i ↦ t ↑i
⊢ MeasurableSet (Set.univ.pi fun i ↦ t ↑i)

Tactic:
any_goals fun_prop

Goal state after:
case hf
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
mX : AEMeasurable (fun ω i ↦ X i ω) P
h : ∀ (s : Finset ι), iIndepFun (s.restrict X) P
this✝ : IsProbabilityMeasure P
x✝ : ∀ (i : ι), IsProbabilityMeasure (map (fun x ↦ X i x) P)
s : Finset ι
t : (i : ι) → Set (𝓧 i)
ht : ∀ (i : ι), MeasurableSet (t i)
this : (↑s).pi t = s.restrict ⁻¹' Set.univ.pi fun i ↦ t ↑i
⊢ AEMeasurable (fun ω i ↦ X i ω) P

case hs
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
mX : AEMeasurable (fun ω i ↦ X i ω) P
h : ∀ (s : Finset ι), iIndepFun (s.restrict X) P
this✝ : IsProbabilityMeasure P
x✝ : ∀ (i : ι), IsProbabilityMeasure (map (fun x ↦ X i x) P)
s : Finset ι
t : (i : ι) → Set (𝓧 i)
ht : ∀ (i : ι), MeasurableSet (t i)
this : (↑s).pi t = s.restrict ⁻¹' Set.univ.pi fun i ↦ t ↑i
⊢ MeasurableSet (Set.univ.pi fun i ↦ t ↑i)
Module: Mathlib.Probability.IdentDistribIndep

Goal state before:
pp: Ω : Type u_1
Ω' : Type u_2
E : Type u_4
F : Type u_5
mΩ : MeasurableSpace Ω
mΩ' : MeasurableSpace Ω'
mE : MeasurableSpace E
mF : MeasurableSpace F
μ : Measure Ω
ν : Measure Ω'
inst✝ : IsFiniteMeasure μ
X : Ω → E
Y : Ω → F
Z : Ω' → E
W : Ω' → F
hXZ : IdentDistrib X Z μ ν
hYW : IdentDistrib Y W μ ν
hXY : X ⟂ᵢ[μ] Y
hZW : Z ⟂ᵢ[ν] W
⊢ IsFiniteMeasure (Measure.map X μ)

Tactic:
infer_instance

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

Goal state before:
pp: Ω : Type u_1
F : Type u_2
m mΩ : MeasurableSpace Ω
inst✝¹ : StandardBorelSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
h : Nonempty Ω
⊢ IsMarkovKernel ((condDistrib id id μ).comap id ⋯)

Tactic:
infer_instance

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

Goal state before:
pp: ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
j : κ i
⊢ ∀ (i_1 : κ i), IsProbabilityMeasure (map (X i i_1) (μ i i_1))

pp: case refine_2.hf
ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
j : κ i
⊢ ∀ (i_1 : κ i), Measurable (X i i_1)

pp: ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
j : κ i
⊢ ∀ (i : ι), IsProbabilityMeasure (map (fun f j ↦ X i j (f j)) (infinitePi (μ i)))

pp: case refine_2
ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
j : κ i
⊢ ∀ (i : ι), Measurable fun f j ↦ X i j (f j)

Tactic:
any_goals fun_prop

Goal state after:
ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
j : κ i
⊢ ∀ (i_1 : κ i), IsProbabilityMeasure (map (X i i_1) (μ i i_1))

ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
j : κ i
⊢ ∀ (i : ι), IsProbabilityMeasure (map (fun f j ↦ X i j (f j)) (infinitePi (μ i)))
Module: Mathlib.Probability.Independence.InfinitePi

Goal state before:
pp: case refine_2.hf
ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
⊢ ∀ (i_1 : κ i), Measurable (X i i_1)

pp: ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
⊢ ∀ (i : ι), IsProbabilityMeasure (map (fun f j ↦ X i j (f j)) (infinitePi (μ i)))

pp: case refine_2
ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
⊢ ∀ (i : ι), Measurable fun f j ↦ X i j (f j)

Tactic:
any_goals fun_prop

Goal state after:
ι : Type u_1
κ : ι → Type u_4
𝓧 : (i : ι) → κ i → Type u_5
m𝓧 : (i : ι) → (j : κ i) → MeasurableSpace (𝓧 i j)
Ω : (i : ι) → κ i → Type u_6
mΩ : (i : ι) → (j : κ i) → MeasurableSpace (Ω i j)
X : (i : ι) → (j : κ i) → Ω i j → 𝓧 i j
μ : (i : ι) → (j : κ i) → Measure (Ω i j)
inst✝ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
mX : ∀ (i : ι) (j : κ i), Measurable (X i j)
i : ι
⊢ ∀ (i : ι), IsProbabilityMeasure (map (fun f j ↦ X i j (f j)) (infinitePi (μ i)))
Module: Mathlib.Probability.Kernel.Condexp

Goal state before:
pp: case pos
Ω : Type u_1
F : Type u_2
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
s : Set Ω
inst✝² : NormedAddCommGroup F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hs : MeasurableSet s
f : Ω → F
hf : Integrable f μ
hμs : μ s = 0
⊢ μ[f | MeasurableSpace.generateFrom {s}] =ᵐ[μ.restrict s] fun x ↦ ∫ (x : Ω), f x ∂μ[|s]

Tactic:
rw [Measure.restrict_eq_zero.2 hμs]

Goal state after:
case pos
Ω : Type u_1
F : Type u_2
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
s : Set Ω
inst✝² : NormedAddCommGroup F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hs : MeasurableSet s
f : Ω → F
hf : Integrable f μ
hμs : μ s = 0
⊢ μ[f | MeasurableSpace.generateFrom {s}] =ᵐ[0] fun x ↦ ∫ (x : Ω), f x ∂μ[|s]
Module: Mathlib.Probability.Kernel.Condexp

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝¹ : IsFiniteMeasure μ
s t : Set Ω
inst✝ : StandardBorelSpace Ω
hs : MeasurableSet s
ht : MeasurableSet t
⊢ ∀ᵐ (ω : Ω) ∂μ.restrict s, ((condExpKernel μ (MeasurableSpace.generateFrom {s})) ω) t = μ[t | s]

Tactic:
have : (fun ω ↦ (condExpKernel μ (generateFrom {s}) ω).real t) =ᵐ[μ.restrict s]
      μ⟦t | generateFrom {s}⟧ :=
    ae_restrict_le <| condExpKernel_ae_eq_condExp
      (generateFrom_singleton_le hs) ht
  filter_upwards [condExp_set_generateFrom_singleton hs ht, this] with ω hω₁ hω₂
  rwa [hω₁, measureReal_def, measureReal_def,
    ENNReal.toReal_eq_toReal_iff' (measure_ne_top _ t) (measure_ne_top _ t)] at hω₂

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

Goal state before:
pp: Ω : Type u_2
m m0 : MeasurableSpace Ω
μ : Measure Ω
inst✝ : StandardBorelSpace Ω
hm : m ≤ m0
hμ : IsFiniteMeasure μ
t : Set Ω
ht : MeasurableSet t
h_indep : CondIndepSet m hm t t μ
this : ∀ (a : Ω), IsFiniteMeasure ((condExpKernel μ m) a)
h : ∀ᵐ (x : Ω) ∂μ, ((condExpKernel μ m) x) t = 0 ∨ ((condExpKernel μ m) x) t = 1
ω : Ω
hω_eq : ((condExpKernel μ m) ω).real t = μ[t.indicator fun ω ↦ 1 | m] ω
hω : ((condExpKernel μ m) ω) t = 0 ∨ ((condExpKernel μ m) ω) t = 1
⊢ μ[t.indicator fun ω ↦ 1 | m] ω = 0 ∨ μ[t.indicator fun ω ↦ 1 | m] ω = 1

Tactic:
rwa [← hω_eq, measureReal_eq_zero_iff, measureReal_def, ENNReal.toReal_eq_one_iff]

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

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
s : ι → MeasurableSpace Ω
m0 : MeasurableSpace Ω
κ : Kernel α Ω
μα : Measure α
β : Type u_4
p : Set ι → Prop
f : Filter ι
ns : β → Set ι
h_le : ∀ (n : ι), s n ≤ m0
h_indep : iIndep s κ μα
hf : ∀ (t : Set ι), p t → tᶜ ∈ f
hns : Directed (fun x1 x2 ↦ x1 ⊆ x2) ns
hnsp : ∀ (a : β), p (ns a)
hns_univ : ∀ (n : ι), ∃ a, n ∈ ns a
t : Set Ω
ht_tail : MeasurableSet t
a : α
ha : IsProbabilityMeasure (κ a)
⊢ IsFiniteMeasure (κ a)

Tactic:
infer_instance

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

Goal state before:
pp: Ω : Type u_2
ι : Type u_3
s : ι → MeasurableSpace Ω
m m0 : MeasurableSpace Ω
μ : Measure Ω
β : Type u_4
p : Set ι → Prop
f : Filter ι
ns : β → Set ι
inst✝¹ : StandardBorelSpace Ω
hm : m ≤ m0
inst✝ : IsFiniteMeasure μ
h_le : ∀ (n : ι), s n ≤ m0
h_indep : iCondIndep m hm s μ
hf : ∀ (t : Set ι), p t → tᶜ ∈ f
hns : Directed (fun x1 x2 ↦ x1 ⊆ x2) ns
hnsp : ∀ (a : β), p (ns a)
hns_univ : ∀ (n : ι), ∃ a, n ∈ ns a
t : Set Ω
ht_tail : MeasurableSet t
h : ∀ᵐ (x : Ω) ∂μ, ((condExpKernel μ m) x) t = 0 ∨ ((condExpKernel μ m) x) t = 1
ht : MeasurableSet t
ω : Ω
hω_eq : ((condExpKernel μ m) ω).real t = μ[t.indicator fun ω ↦ 1 | m] ω
hω : ((condExpKernel μ m) ω) t = 0 ∨ ((condExpKernel μ m) ω) t = 1
⊢ μ[t.indicator fun ω ↦ 1 | m] ω = 0 ∨ μ[t.indicator fun ω ↦ 1 | m] ω = 1

Tactic:
rwa [← hω_eq, measureReal_eq_zero_iff, measureReal_def, ENNReal.toReal_eq_one_iff]

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

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
s : ι → MeasurableSpace Ω
m0 : MeasurableSpace Ω
κ : Kernel α Ω
μα : Measure α
inst✝² : SemilatticeSup ι
inst✝¹ : NoMaxOrder ι
inst✝ : Nonempty ι
h_le : ∀ (n : ι), s n ≤ m0
h_indep : iIndep s κ μα
t : Set Ω
ht_tail : MeasurableSet t
a : α
ha : IsProbabilityMeasure (κ a)
⊢ IsFiniteMeasure (κ a)

Tactic:
infer_instance

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

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

Tactic:
infer_instance

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

Goal state before:
pp: X : SFinKer
⊢ IsMarkovKernel Kernel.id

Tactic:
infer_instance

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

Goal state before:
pp: X✝ Y✝ Z✝ : SFinKer
κ : X✝ ⟶ Y✝
η : Y✝ ⟶ Z✝
hκ : StochHom κ
hη : StochHom η
⊢ IsMarkovKernel (η.hom ∘ₖ κ.hom)

Tactic:
infer_instance

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

Goal state before:
pp: X Y Z : SFinKer
κ : Y ⟶ Z
hκ : StochHom κ
⊢ IsMarkovKernel (Kernel.id ∥ₖ κ.hom)

Tactic:
infer_instance

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

Goal state before:
pp: X₁✝ X₂✝ : SFinKer
κ : X₁✝ ⟶ X₂✝
hκ : StochHom κ
Y : SFinKer
⊢ IsMarkovKernel (κ.hom ∥ₖ Kernel.id)

Tactic:
infer_instance

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

Goal state before:
pp: X : SFinKer
⊢ IsMarkovKernel (Kernel.discard X.carrier)

Tactic:
infer_instance

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

Goal state before:
pp: X : SFinKer
⊢ IsMarkovKernel (copy X.carrier)

Tactic:
infer_instance

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

Goal state before:
pp: X : SFinKer
f₁ : X.carrier → X.carrier × PUnit.{u + 1} := fun x ↦ (x, PUnit.unit)
hf₁ : Measurable f₁
hf₂ : Measurable Prod.fst
⊢ IsSFiniteKernel (Kernel.id.map Prod.fst)

Tactic:
infer_instance

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

Goal state before:
pp: X : SFinKer
f₁ : X.carrier → X.carrier × PUnit.{u + 1} := fun x ↦ (x, PUnit.unit)
hf₁ : Measurable f₁
hf₂ : Measurable Prod.fst
⊢ IsSFiniteKernel (Kernel.id.map f₁)

Tactic:
infer_instance

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

Goal state before:
pp: X Y : SFinKer
⊢ IsSFiniteKernel (Kernel.deterministic Prod.swap ⋯)

Tactic:
infer_instance

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

Goal state before:
pp: case refine_2
X : Type u_1
𝓑 𝓧 : MeasurableSpace X
π : Kernel X X
f g : X → ℝ≥0∞
hπ : π.IsProper
h𝓑𝓧 : 𝓑 ≤ 𝓧
hf : Measurable f
hg : Measurable g
x₀ : X
g₁ g₂ : X → ℝ≥0∞
a✝ : Measurable g₁
hg₂_meas : Measurable g₂
hg₁ : ∫⁻ (x : X), g₁ x * f x ∂π x₀ = g₁ x₀ * ∫⁻ (x : X), f x ∂π x₀
hg₂ : ∫⁻ (x : X), g₂ x * f x ∂π x₀ = g₂ x₀ * ∫⁻ (x : X), f x ∂π x₀
⊢ g₁ x₀ * ∫⁻ (x : X), f x ∂π x₀ + ∫⁻ (a : X), g₂ a * f a ∂π x₀ =
    g₁ x₀ * ∫⁻ (x : X), f x ∂π x₀ + g₂ x₀ * ∫⁻ (x : X), f x ∂π x₀

pp: case refine_2.hg
X : Type u_1
𝓑 𝓧 : MeasurableSpace X
π : Kernel X X
f g : X → ℝ≥0∞
hπ : π.IsProper
h𝓑𝓧 : 𝓑 ≤ 𝓧
hf : Measurable f
hg : Measurable g
x₀ : X
g₁ g₂ : X → ℝ≥0∞
a✝ : Measurable g₁
hg₂_meas : Measurable g₂
hg₁ : ∫⁻ (x : X), g₁ x * f x ∂π x₀ = g₁ x₀ * ∫⁻ (x : X), f x ∂π x₀
hg₂ : ∫⁻ (x : X), g₂ x * f x ∂π x₀ = g₂ x₀ * ∫⁻ (x : X), f x ∂π x₀
⊢ Measurable fun x ↦ g₂ x * f x

Tactic:
hg₂

Goal state after:
case refine_2
X : Type u_1
𝓑 𝓧 : MeasurableSpace X
π : Kernel X X
f g : X → ℝ≥0∞
hπ : π.IsProper
h𝓑𝓧 : 𝓑 ≤ 𝓧
hf : Measurable f
hg : Measurable g
x₀ : X
g₁ g₂ : X → ℝ≥0∞
a✝ : Measurable g₁
hg₂_meas : Measurable g₂
hg₁ : ∫⁻ (x : X), g₁ x * f x ∂π x₀ = g₁ x₀ * ∫⁻ (x : X), f x ∂π x₀
hg₂ : ∫⁻ (x : X), g₂ x * f x ∂π x₀ = g₂ x₀ * ∫⁻ (x : X), f x ∂π x₀
⊢ g₁ x₀ * ∫⁻ (x : X), f x ∂π x₀ + g₂ x₀ * ∫⁻ (x : X), f x ∂π x₀ =
    g₁ x₀ * ∫⁻ (x : X), f x ∂π x₀ + g₂ x₀ * ∫⁻ (x : X), f x ∂π x₀

case refine_2.hg
X : Type u_1
𝓑 𝓧 : MeasurableSpace X
π : Kernel X X
f g : X → ℝ≥0∞
hπ : π.IsProper
h𝓑𝓧 : 𝓑 ≤ 𝓧
hf : Measurable f
hg : Measurable g
x₀ : X
g₁ g₂ : X → ℝ≥0∞
a✝ : Measurable g₁
hg₂_meas : Measurable g₂
hg₁ : ∫⁻ (x : X), g₁ x * f x ∂π x₀ = g₁ x₀ * ∫⁻ (x : X), f x ∂π x₀
hg₂ : ∫⁻ (x : X), g₂ x * f x ∂π x₀ = g₂ x₀ * ∫⁻ (x : X), f x ∂π x₀
⊢ Measurable fun x ↦ g₂ x * f x
Module: Mathlib.Probability.Kernel.Category.SFinKer

Goal state before:
pp: X : SFinKer
⊢ IsSFiniteKernel (Kernel.deterministic (fun x ↦ PUnit.unit) ⋯)

Tactic:
infer_instance

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

Goal state before:
pp: X : SFinKer
⊢ IsSFiniteKernel (Kernel.deterministic Function.diag ⋯)

Tactic:
infer_instance

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
hk_meas : ∀ {s : Set γ}, MeasurableSet s → MeasurableSet (k ⁻¹' s)
s : Set γ
t : Set β
u : Set β'
hs : MeasurableSet s
ht : MeasurableSet t
hu : MeasurableSet u
⊢ μ ((fun ω ↦ (k ω, f ω, g ω)) ⁻¹' s ×ˢ t ×ˢ u) = μ ((fun ω ↦ (ω, f ω, g ω)) ⁻¹' (k ⁻¹' s) ×ˢ t ×ˢ u)

Tactic:
simp [Set.mk_preimage_prod]

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

Goal state before:
pp: X : Type u_1
Y : Type u_2
mX : MeasurableSpace X
inst✝² : Nonempty Y
mY : MeasurableSpace Y
inst✝¹ : StandardBorelSpace Y
κ : Kernel X Y
inst✝ : IsMarkovKernel κ
g : Y → ↑I := sigmoid ∘ embeddingReal Y
hg : MeasurableEmbedding (sigmoid ∘ embeddingReal Y)
hκg : IsMarkovKernel (κ.map g)
hg'κ : κ = (κ.map g).map hg.invFun
f' : X → ↑I → ↑I
hf' : Measurable (uncurry f')
hf'κ : ∀ (a : X), Measure.map (f' a) volume = (κ.map g) a
⊢ ∃ f, Measurable (uncurry f) ∧ ∀ (a : X), Measure.map (f a) volume = κ a

Tactic:
refine ⟨fun a u ↦ hg.invFun (f' a u), by fun_prop, fun a ↦ ?_⟩

Goal state after:
X : Type u_1
Y : Type u_2
mX : MeasurableSpace X
inst✝² : Nonempty Y
mY : MeasurableSpace Y
inst✝¹ : StandardBorelSpace Y
κ : Kernel X Y
inst✝ : IsMarkovKernel κ
g : Y → ↑I := sigmoid ∘ embeddingReal Y
hg : MeasurableEmbedding (sigmoid ∘ embeddingReal Y)
hκg : IsMarkovKernel (κ.map g)
hg'κ : κ = (κ.map g).map hg.invFun
f' : X → ↑I → ↑I
hf' : Measurable (uncurry f')
hf'κ : ∀ (a : X), Measure.map (f' a) volume = (κ.map g) a
a : X
⊢ Measure.map ((fun a u ↦ hg.invFun (f' a u)) a) volume = κ a
Module: Mathlib.Probability.Moments.Tilted

Goal state before:
pp: case inr
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
hμ : NeZero μ
⊢ (μ.tilted fun x ↦ t * X x) s = ENNReal.ofReal (∫ (a : Ω) in s, rexp (t * X a - cgf X μ t) ∂μ)

Tactic:
· simp_rw [tilted_mul_apply_eq_ofReal_integral_mgf' hs, exp_sub]
    rwa [exp_cgf]

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

Goal state before:
pp: case neg
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
t : ℝ
ht : t ∈ interior (integrableExpSet X μ)
p : ℝ≥0
hX : AEMeasurable X μ
hp : ¬p = 0
⊢ Integrable (fun x ↦ rexp (t * X x) * |X x| ^ ↑p) μ

Tactic:
mul_comm

Goal state after:
case neg
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
X : Ω → ℝ
t : ℝ
ht : t ∈ interior (integrableExpSet X μ)
p : ℝ≥0
hX : AEMeasurable X μ
hp : ¬p = 0
⊢ Integrable (fun x ↦ |X x| ^ ↑p * rexp (t * X x)) μ
Module: Mathlib.Probability.Process.Kolmogorov

Goal state before:
pp: T : Type u_1
Ω : Type u_2
E : Type u_3
inst✝⁴ : PseudoEMetricSpace T
mΩ : MeasurableSpace Ω
inst✝³ : PseudoEMetricSpace E
p q : ℝ
M : ℝ≥0
P : Measure Ω
X : T → Ω → E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
inst✝ : SecondCountableTopology E
h_meas : ∀ (s : T), Measurable (X s)
h_kol : ∀ (s t : T), ∫⁻ (ω : Ω), edist (X s ω) (X t ω) ^ p ∂P ≤ ↑M * edist s t ^ q
hp : 0 < p
hq : 0 < q
s t : T
⊢ Measurable fun ω ↦ (X s ω, X t ω)

Tactic:
suffices Measurable (fun ω ↦ (X s ω, X t ω)) by
      rwa [Prod.borelSpace.measurable_eq] at this
    fun_prop

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
r t : ℝ
⊢ Integrable (fun ω ↦ rexp (t * (r * X ω))) (⇑κ ∘ₘ ν)

Tactic:
simp_rw [← mul_assoc]

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
r t : ℝ
⊢ Integrable (fun ω ↦ rexp (t * r * X ω)) (⇑κ ∘ₘ ν)
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
r : ℝ
ω : Ω'
hω : ∀ (t : ℝ), mgf X (κ ω) t ≤ rexp (↑c * t ^ 2 / 2)
t : ℝ
⊢ mgf X (κ ω) (r * t) ≤ rexp (↑(NNReal.mk (r ^ 2) ⋯ * c) * t ^ 2 / 2)

Tactic:
mul_comm

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
r : ℝ
ω : Ω'
hω : ∀ (t : ℝ), mgf X (κ ω) t ≤ rexp (↑c * t ^ 2 / 2)
t : ℝ
⊢ mgf X (κ ω) (t * r) ≤ rexp (↑(NNReal.mk (r ^ 2) ⋯ * c) * t ^ 2 / 2)
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
⊢ 2.HolderTriple 2 1

Tactic:
infer_instance

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:
linarith [h x]

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 : ℕ
hKN : K ≤ N
ρ : Measure ℝ := Measure.map X ℙ
this : IsProbabilityMeasure ρ
⊢ ∫ (x : ℝ) in 0..↑N, x + 1 ∂ρ = ∫ (x : ℝ) in 0..↑N, x ∂ρ + ∫ (x : ℝ) in 0..↑N, 1 ∂ρ

Tactic:
rw [intervalIntegral.integral_add]
        · exact continuous_id.intervalIntegrable _ _
        · exact continuous_const.intervalIntegrable _ _

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 ↦ ?_⟩⟩
  · rw [← Function.id_comp X]
    exact .of_map hX h
  · rw [integrable_map_measure (by fun_prop) hX]
    exact h.integrable_exp_mul t
  · rw [mgf_id_map hX]
    exact h.mgf_le t

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
⊢ 2.HolderTriple 2 1

Tactic:
infer_instance

Goal state after: