LeanMachineLearning exposition

ProbabilityTheory.IndepFun.of_measurable🔗

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of_measurable🔗

LemmaProbabilityTheory.IndepFun.of_measurable
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🔗theorem
ProbabilityTheory.IndepFun.of_measurable.{u_1, u_3, u_4, u_5, u_6}
  {α : Type u_1} {γ : Type u_3} {δ : Type u_4} {γ' : Type u_5}
  {δ' : Type u_6} {mα : MeasurableSpace α} {mγ : MeasurableSpace γ}
  {mδ : MeasurableSpace δ} {mγ' : MeasurableSpace γ'}
  {mδ' : MeasurableSpace δ'} [StandardBorelSpace δ'] [Nonempty δ']
  [StandardBorelSpace γ'] [Nonempty γ'] {μ : MeasureTheory.Measure α}
  {Y : α → γ} {Z : α → δ} {Y' : α → γ'} {Z' : α → δ'}
  (h_indep : IndepFun Y Z μ) (hY_meas : Measurable Y')
  (hZ_meas : Measurable Z') : IndepFun Y' Z' μ
ProbabilityTheory.IndepFun.of_measurable.{u_1,
    u_3, u_4, u_5, u_6}
  {α : Type u_1} {γ : Type u_3}
  {δ : Type u_4} {γ' : Type u_5}
  {δ' : Type u_6} {mα : MeasurableSpace α}
  {mγ : MeasurableSpace γ}
  {mδ : MeasurableSpace δ}
  {mγ' : MeasurableSpace γ'}
  {mδ' : MeasurableSpace δ'}
  [StandardBorelSpace δ'] [Nonempty δ']
  [StandardBorelSpace γ'] [Nonempty γ']
  {μ : MeasureTheory.Measure α}
  {Y : α → γ} {Z : α → δ} {Y' : α → γ'}
  {Z' : α → δ'} (h_indep : IndepFun Y Z μ)
  (hY_meas : Measurable Y')
  (hZ_meas : Measurable Z') :
  IndepFun Y' Z' μ

Code

lemma IndepFun.of_measurable (h_indep : Y ⟂ᵢ[μ] Z)
    (hY_meas : Measurable[mγ.comap Y] Y') (hZ_meas : Measurable[mδ.comap Z] Z') :
    Y' ⟂ᵢ[μ] Z'

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Proof
by
  obtain ⟨φ, hφ_meas, h_eqY⟩ : ∃ φ, Measurable φ ∧ Y' = φ ∘ Y := hY_meas.exists_eq_measurable_comp
  obtain ⟨ψ, hψ_meas, h_eqZ⟩ : ∃ ψ, Measurable ψ ∧ Z' = ψ ∘ Z := hZ_meas.exists_eq_measurable_comp
  rw [h_eqY, h_eqZ]
  exact h_indep.comp hφ_meas hψ_meas