awhecmu/canonical-drafter-extract-mathlib huggingface dataset:
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b : ℕ
hab : a ≤ b
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_f :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X)) f
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
i_f' :
  @Integrable.{u_2, u_1} E _ _ _ (MeasurableSpace.pi (X := fun (i : ↥(Iic b)) ↦ X (↑i : ℕ)))
    (fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
      @integral _ _ _ _ (MeasurableSpace.pi (X := X))
        ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x) fun (y : (n : ℕ) → X n) ↦
        f y)
    (Measure.map (frestrictLe (π := X) b)
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀))
⊢ condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
      f =ᶠ[ae (F := Measure ((n : ℕ) → X n))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀ : Measure ((n : ℕ) → X n))]
    fun (x : (n : ℕ) → X n) ↦
    @integral _ _ _ _ (MeasurableSpace.pi (X := X))
      ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) (frestrictLe (π := X) b x))
      fun (y : (n : ℕ) → X n) ↦ f y

Tactic:
ae_eq_condExp_of_forall_setIntegral_eq (piLE.le _) i_f
    (fun s _ _ ↦ i_f'.comp_aemeasurable (measurable_frestrictLe b).aemeasurable |>.integrableOn)
    ?_ ?_ |>.symm

Premises used: MeasureTheory.Integrable.comp_aemeasurable, Measurable.aemeasurable, MeasureTheory.Filtration.piLE, MeasureTheory.Filtration.le, Preorder.measurable_frestrictLe, MeasureTheory.Integrable.integrableOn, MeasureTheory.ae_eq_condExp_of_forall_setIntegral_eq, Filter.EventuallyEq.symm
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b : ℕ
hab : a ≤ b
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_f :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X)) f
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
i_f' :
  @Integrable.{u_2, u_1} E _ _ _ (MeasurableSpace.pi (X := fun (i : ↥(Iic b)) ↦ X (↑i : ℕ)))
    (fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
      @integral _ _ _ _ (MeasurableSpace.pi (X := X))
        ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x) fun (y : (n : ℕ) → X n) ↦
        f y)
    (Measure.map (frestrictLe (π := X) b)
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀))
refine_2 :
  AEStronglyMeasurable.{u_1, u_2} (α := (i : ℕ) → X i) (β := E) (m₀ := MeasurableSpace.pi (X := X))
    ((fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
        @integral _ _ _ _ (MeasurableSpace.pi (X := X))
          ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x)
          fun (y : (n : ℕ) → X n) ↦ f y) ∘
      frestrictLe (π := X) b)
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
⊢ AEStronglyMeasurable.{u_1, u_2} (α := (i : ℕ) → X i) (β := E) (m₀ := MeasurableSpace.pi (X := X))
    ((fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
        @integral _ _ _ _ (MeasurableSpace.pi (X := X))
          ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x)
          fun (y : (n : ℕ) → X n) ↦ f y) ∘
      frestrictLe (π := X) b)
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)

Tactic:
rw [piLE_eq_comap_frestrictLe]

Premises used: MeasureTheory.Filtration.piLE_eq_comap_frestrictLe
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b : ℕ
hab : a ≤ b
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_f :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X)) f
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
i_f' :
  @Integrable.{u_2, u_1} E _ _ _ (MeasurableSpace.pi (X := fun (i : ↥(Iic b)) ↦ X (↑i : ℕ)))
    (fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
      @integral _ _ _ _ (MeasurableSpace.pi (X := X))
        ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x) fun (y : (n : ℕ) → X n) ↦
        f y)
    (Measure.map (frestrictLe (π := X) b)
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀))
t : Set ((i : ↥(Iic b)) → X (↑i : ℕ))
mt : MeasurableSet t
refine_1 : Measurable.{u_1, u_1} (α := (i : ℕ) → X i) (β := (i : ↥(Iic b)) → X (↑i : ℕ)) (frestrictLe (π := X) b)
refine_1₁ :
  AEMeasurable.{u_1, u_1} (α := (i : ℕ) → X i) (β := (i : ↥(Iic b)) → X (↑i : ℕ)) (_m := MeasurableSpace.pi (X := X))
    (frestrictLe (π := X) b) ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
⊢ Eq.{u_2 + 1} (α := E)
    (@integral _ _ _ _ (MeasurableSpace.pi (X := X))
      (Measure.restrict ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
        (frestrictLe (π := X) b ⁻¹' t))
      fun (x : (i : ℕ) → X i) ↦
      @integral _ _ _ _ (MeasurableSpace.pi (X := X))
        ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) (frestrictLe (π := X) b x))
        fun (y : (n : ℕ) → X n) ↦ f y)
    (@integral _ _ _ _ (MeasurableSpace.pi (X := X))
      (Measure.restrict ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
        (frestrictLe (π := X) b ⁻¹' t))
      fun (y : (n : ℕ) → X n) ↦ f y)

Tactic:
rw [← setIntegral_map mt i_f'.1, ← map_apply, traj_map_frestrictLe,
      setIntegral_traj_partialTraj hab i_f mt]

Premises used: ProbabilityTheory.Kernel.map_apply, MeasureTheory.setIntegral_map, And.left, ProbabilityTheory.Kernel.traj_map_frestrictLe, ProbabilityTheory.Kernel.setIntegral_traj_partialTraj
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b : ℕ
hab : a ≤ b
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_f :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X)) f
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
i_f' :
  @Integrable.{u_2, u_1} E _ _ _ (MeasurableSpace.pi (X := fun (i : ↥(Iic b)) ↦ X (↑i : ℕ)))
    (fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
      @integral _ _ _ _ (MeasurableSpace.pi (X := X))
        ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x) fun (y : (n : ℕ) → X n) ↦
        f y)
    (Measure.map (frestrictLe (π := X) b)
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀))
t : Set ((i : ↥(Iic b)) → X (↑i : ℕ))
mt : MeasurableSet t
⊢ Measurable.{u_1, u_1} (α := (i : ℕ) → X i) (β := (i : ↥(Iic b)) → X (↑i : ℕ)) (frestrictLe (π := X) b)

Tactic:
fun_prop
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b : ℕ
hab : a ≤ b
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_f :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X)) f
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
i_f' :
  @Integrable.{u_2, u_1} E _ _ _ (MeasurableSpace.pi (X := fun (i : ↥(Iic b)) ↦ X (↑i : ℕ)))
    (fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
      @integral _ _ _ _ (MeasurableSpace.pi (X := X))
        ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x) fun (y : (n : ℕ) → X n) ↦
        f y)
    (Measure.map (frestrictLe (π := X) b)
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀))
t : Set ((i : ↥(Iic b)) → X (↑i : ℕ))
mt : MeasurableSet t
⊢ AEMeasurable.{u_1, u_1} (α := (i : ℕ) → X i) (β := (i : ↥(Iic b)) → X (↑i : ℕ)) (_m := MeasurableSpace.pi (X := X))
    (frestrictLe (π := X) b) ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)

Tactic:
fun_prop
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b : ℕ
hab : a ≤ b
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_f :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X)) f
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
i_f' :
  @Integrable.{u_2, u_1} E _ _ _ (MeasurableSpace.pi (X := fun (i : ↥(Iic b)) ↦ X (↑i : ℕ)))
    (fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
      @integral _ _ _ _ (MeasurableSpace.pi (X := X))
        ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x) fun (y : (n : ℕ) → X n) ↦
        f y)
    (Measure.map (frestrictLe (π := X) b)
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀))
⊢ AEStronglyMeasurable.{u_1, u_2} (α := (i : ℕ) → X i) (β := E) (m₀ := MeasurableSpace.pi (X := X))
    ((fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
        @integral _ _ _ _ (MeasurableSpace.pi (X := X))
          ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x)
          fun (y : (n : ℕ) → X n) ↦ f y) ∘
      frestrictLe (π := X) b)
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)

Tactic:
(i_f'.1.comp_ae_measurable' (measurable_frestrictLe b).aemeasurable)

Premises used: Measurable.aemeasurable, And.left, MeasureTheory.AEStronglyMeasurable.comp_ae_measurable', Preorder.measurable_frestrictLe
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b : ℕ
hab : a ≤ b
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_f :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X)) f
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
i_f' :
  @Integrable.{u_2, u_1} E _ _ _ (MeasurableSpace.pi (X := fun (i : ↥(Iic b)) ↦ X (↑i : ℕ)))
    (fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
      @integral _ _ _ _ (MeasurableSpace.pi (X := X))
        ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x) fun (y : (n : ℕ) → X n) ↦
        f y)
    (Measure.map (frestrictLe (π := X) b)
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀))
⊢ AEStronglyMeasurable.{u_1, u_2} (α := (i : ℕ) → X i) (β := E) (m₀ := MeasurableSpace.pi (X := X))
    ((fun (x : (i : ↥(Iic b)) → X (↑i : ℕ)) ↦
        @integral _ _ _ _ (MeasurableSpace.pi (X := X))
          ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x)
          fun (y : (n : ℕ) → X n) ↦ f y) ∘
      frestrictLe (π := X) b)
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)

Tactic:
exact (i_f'.1.comp_ae_measurable' (measurable_frestrictLe b).aemeasurable)

Premises used: Measurable.aemeasurable, And.left, MeasureTheory.AEStronglyMeasurable.comp_ae_measurable', Preorder.measurable_frestrictLe
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b c : ℕ
hab : a ≤ b
hbc : b ≤ c
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
⊢ @Integrable _ _ _ _ (MeasurableSpace.pi (X := X))
    (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)

Tactic:
have i_cf : Integrable ((traj κ a x₀)[f | piLE c]) (traj κ a x₀) :=
    integrable_condExp
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b c : ℕ
hab : a ≤ b
hbc : b ≤ c
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_cf :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X))
    (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
⊢ StronglyMeasurable
    (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)

Tactic:
have mcf : StronglyMeasurable ((traj κ a x₀)[f | piLE c]) :=
    stronglyMeasurable_condExp.mono (piLE.le c)
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b c : ℕ
hab : a ≤ b
hbc : b ≤ c
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_cf :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X))
    (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
mcf :
  StronglyMeasurable
    (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
x : (n : ℕ) → X n
h1 :
  condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((n : ℕ) → X n)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
      (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((n : ℕ) → X n)) c) (m₀ := MeasurableSpace.pi (X := X))
        ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
      x =
    condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((n : ℕ) → X n)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f x
h2 :
  condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
      (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
        ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
      x =
    @integral _ _ _ _ (MeasurableSpace.pi (X := X))
      ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) (frestrictLe (π := X) b x))
      fun (y : (n : ℕ) → X n) ↦
      condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
        ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f y
y : (n : ℕ) → X n
h : ∀ i ≤ c, y i = if i ≤ c then y i else x i
⊢ ∀ i ∈ Set.Iic c, y i = updateFinset (π := X) x (Iic c) (frestrictLe (π := X) c y) i

Tactic:
simp only [Set.mem_Iic, updateFinset, mem_Iic, frestrictLe_apply, dite_eq_ite]

Premises used: Function.updateFinset, Finset.mem_Iic, Preorder.frestrictLe_apply, Set.mem_Iic, dite_eq_ite
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b c : ℕ
hab : a ≤ b
hbc : b ≤ c
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_cf :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X))
    (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
mcf :
  StronglyMeasurable
    (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
x : (n : ℕ) → X n
h1 :
  condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((n : ℕ) → X n)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
      (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((n : ℕ) → X n)) c) (m₀ := MeasurableSpace.pi (X := X))
        ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
      x =
    condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((n : ℕ) → X n)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f x
h2 :
  condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
      (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
        ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
      x =
    @integral _ _ _ _ (MeasurableSpace.pi (X := X))
      ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) (frestrictLe (π := X) b x))
      fun (y : (n : ℕ) → X n) ↦
      condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
        ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f y
y : (n : ℕ) → X n
⊢ ∀ i ≤ c, y i = if i ≤ c then y i else x i

Tactic:
fun i hi ↦ (if_pos hi).symm

Premises used: if_pos, Eq.symm
-- Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj
Goal:
X : ℕ → Type u_1
inst : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X (↑i : ℕ)) (X (n + 1))
inst_1 : ∀ (n : ℕ), IsMarkovKernel (κ n)
E : Type u_2
inst_2 : NormedAddCommGroup E
inst_3 : NormedSpace ℝ E
inst_4 : CompleteSpace E
a b c : ℕ
hab : a ≤ b
hbc : b ≤ c
x₀ : (i : ↥(Iic a)) → X (↑i : ℕ)
f : ((n : ℕ) → X n) → E
i_cf :
  @Integrable _ _ _ _ (MeasurableSpace.pi (X := X))
    (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
    ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
mcf :
  StronglyMeasurable
    (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
x : (n : ℕ) → X n
h1 :
  condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((n : ℕ) → X n)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
      (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((n : ℕ) → X n)) c) (m₀ := MeasurableSpace.pi (X := X))
        ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
      x =
    condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((n : ℕ) → X n)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f x
h2 :
  condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) b) (m₀ := MeasurableSpace.pi (X := X))
      ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀)
      (condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
        ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f)
      x =
    @integral _ _ _ _ (MeasurableSpace.pi (X := X))
      ((traj (X := X) κ b : (a : (i : ↥(Iic b)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) (frestrictLe (π := X) b x))
      fun (y : (n : ℕ) → X n) ↦
      condExp ((↑(piLE (X := X)) : ℕ → MeasurableSpace ((i : ℕ) → X i)) c) (m₀ := MeasurableSpace.pi (X := X))
        ((traj (X := X) κ a : (a : (i : ↥(Iic a)) → X (↑i : ℕ)) → Measure ((n : ℕ) → X n)) x₀) f y
y : (n : ℕ) → X n
⊢ ∀ i ≤ c, y i = if i ≤ c then y i else x i

Tactic:
exact fun i hi ↦ (if_pos hi).symm

Premises used: if_pos, Eq.symm