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PFR.Mathlib.Probability.Kernel.Disintegration

Disintegration of kernels in finite spaces #

We can write κ : Kernel S (T × U) as a composition-product (fst κ) ⊗ₖ (condKernel κ) where fst κ : Kernel S T and condKernel : Kernel (S × T) U is defined in this file.

theorem ProbabilityTheory.Kernel.condKernel_apply {S : Type u_2} {T : Type u_3} {U : Type u_4} [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [Countable U] [Nonempty U] [DiscreteMeasurableSpace U] (κ : ProbabilityTheory.Kernel T (S × U)) [ProbabilityTheory.IsFiniteKernel κ] (x : T × S) (hx : (κ x.1) (Prod.fst ⁻¹' {x.2}) 0) :
κ.condKernel x = (κ x.1).condKernel x.2
theorem ProbabilityTheory.Kernel.condKernel_apply' {S : Type u_2} {T : Type u_3} {U : Type u_4} [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [Countable U] [Nonempty U] [DiscreteMeasurableSpace U] (κ : ProbabilityTheory.Kernel T (S × U)) [ProbabilityTheory.IsFiniteKernel κ] (x : T × S) (hx : (κ x.1) (Prod.fst ⁻¹' {x.2}) 0) (s : Set U) :
(κ.condKernel x) s = ((κ x.1) (Prod.fst ⁻¹' {x.2}))⁻¹ * (κ x.1) ({x.2} ×ˢ s)
theorem ProbabilityTheory.Kernel.condKernel_compProd_apply' {S : Type u_2} {T : Type u_3} {U : Type u_4} [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [Countable U] [Nonempty U] [DiscreteMeasurableSpace U] (κ : ProbabilityTheory.Kernel T S) [ProbabilityTheory.IsFiniteKernel κ] (η : ProbabilityTheory.Kernel (T × S) U) [ProbabilityTheory.IsMarkovKernel η] (x : T × S) (hx : (κ x.1) {x.2} 0) {s : Set U} (hs : MeasurableSet s) :
((κ.compProd η).condKernel x) s = (η x) s
theorem ProbabilityTheory.Kernel.condKernel_map_prod_mk_left {S : Type u_2} {T : Type u_3} {U : Type u_4} [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [Countable U] [Nonempty U] [DiscreteMeasurableSpace U] [Countable T] [MeasurableSingletonClass S] [MeasurableSingletonClass T] {V : Type u_5} [Nonempty V] [MeasurableSpace V] [DiscreteMeasurableSpace V] [Countable V] (κ : ProbabilityTheory.Kernel T (S × U)) [ProbabilityTheory.IsMarkovKernel κ] (μ : MeasureTheory.Measure T) [MeasureTheory.IsFiniteMeasure μ] (f : S × UV) :
(κ.map fun (p : S × U) => (p.1, f p)).condKernel =ᵐ[μ.compProd κ.fst] (κ.condKernel.compProd (ProbabilityTheory.Kernel.deterministic (fun (x : (T × S) × U) => f (x.1.2, x.2)) )).snd
theorem ProbabilityTheory.condDistrib_apply' {Ω : Type u_1} {S : Type u_2} {T : Type u_3} [mΩ : MeasurableSpace Ω] [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSingletonClass T] {X : ΩS} {Y : ΩT} [Nonempty S] (hX : Measurable X) (hY : Measurable Y) (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsFiniteMeasure μ] (x : T) (hYx : μ (Y ⁻¹' {x}) 0) {s : Set S} (hs : MeasurableSet s) :
((ProbabilityTheory.condDistrib X Y μ) x) s = (μ (Y ⁻¹' {x}))⁻¹ * μ (Y ⁻¹' {x} X ⁻¹' s)
theorem ProbabilityTheory.condDistrib_fst_of_ne_zero {Ω : Type u_1} {S : Type u_2} {T : Type u_3} {U : Type u_4} [mΩ : MeasurableSpace Ω] [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass T] [Countable U] [DiscreteMeasurableSpace U] {X : ΩS} {Y : ΩT} {Z : ΩU} [Countable T] [Nonempty T] [Nonempty S] (hX : Measurable X) (hY : Measurable Y) (hZ : Measurable Z) (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsFiniteMeasure μ] (u : U) (hu : μ (Z ⁻¹' {u}) 0) :
(ProbabilityTheory.condDistrib (fun (a : Ω) => (X a, Y a)) Z μ).fst u = (ProbabilityTheory.condDistrib X Z μ) u
theorem ProbabilityTheory.condDistrib_fst_ae_eq {Ω : Type u_1} {S : Type u_2} {T : Type u_3} {U : Type u_4} [mΩ : MeasurableSpace Ω] [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass T] [Countable U] [DiscreteMeasurableSpace U] {X : ΩS} {Y : ΩT} {Z : ΩU} [Countable T] [Nonempty T] [Nonempty S] (hX : Measurable X) (hY : Measurable Y) (hZ : Measurable Z) (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsFiniteMeasure μ] :
(ProbabilityTheory.condDistrib (fun (a : Ω) => (X a, Y a)) Z μ).fst =ᵐ[MeasureTheory.Measure.map Z μ] (ProbabilityTheory.condDistrib X Z μ)
theorem ProbabilityTheory.condDistrib_snd_of_ne_zero {Ω : Type u_1} {S : Type u_2} {T : Type u_3} {U : Type u_4} [mΩ : MeasurableSpace Ω] [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass T] [Countable U] [DiscreteMeasurableSpace U] {X : ΩS} {Y : ΩT} {Z : ΩU} [Countable T] [Nonempty T] [Nonempty S] (hX : Measurable X) (hY : Measurable Y) (hZ : Measurable Z) (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsFiniteMeasure μ] (u : U) (hu : μ (Z ⁻¹' {u}) 0) :
(ProbabilityTheory.condDistrib (fun (a : Ω) => (X a, Y a)) Z μ).snd u = (ProbabilityTheory.condDistrib Y Z μ) u
theorem ProbabilityTheory.condDistrib_snd_ae_eq {Ω : Type u_1} {S : Type u_2} {T : Type u_3} {U : Type u_4} [mΩ : MeasurableSpace Ω] [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass T] [Countable U] [DiscreteMeasurableSpace U] {X : ΩS} {Y : ΩT} {Z : ΩU} [Countable T] [Nonempty T] [Nonempty S] (hX : Measurable X) (hY : Measurable Y) (hZ : Measurable Z) (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsFiniteMeasure μ] :
(ProbabilityTheory.condDistrib (fun (a : Ω) => (X a, Y a)) Z μ).snd =ᵐ[MeasureTheory.Measure.map Z μ] (ProbabilityTheory.condDistrib Y Z μ)
theorem ProbabilityTheory.condKernel_condDistrib_ae_eq {Ω : Type u_1} {S : Type u_2} {T : Type u_3} {U : Type u_4} [mΩ : MeasurableSpace Ω] [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass T] [Countable U] [DiscreteMeasurableSpace U] {X : ΩS} {Y : ΩT} {Z : ΩU} [Countable T] [Nonempty T] [Nonempty S] (hX : Measurable X) (hY : Measurable Y) (hZ : Measurable Z) (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsFiniteMeasure μ] :
(ProbabilityTheory.condDistrib (fun (a : Ω) => (X a, Y a)) Z μ).condKernel =ᵐ[MeasureTheory.Measure.map (fun (ω : Ω) => (Z ω, X ω)) μ] (ProbabilityTheory.condDistrib Y (fun (ω : Ω) => (Z ω, X ω)) μ)
theorem ProbabilityTheory.swap_condDistrib_ae_eq {Ω : Type u_1} {S : Type u_2} {T : Type u_3} {U : Type u_4} [mΩ : MeasurableSpace Ω] [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass T] [Countable U] [DiscreteMeasurableSpace U] {X : ΩS} {Y : ΩT} {Z : ΩU} [Countable T] [Nonempty T] (hX : Measurable X) (hY : Measurable Y) (hZ : Measurable Z) (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsFiniteMeasure μ] :
((ProbabilityTheory.condDistrib Y (fun (a : Ω) => (X a, Z a)) μ).comap Prod.swap ) =ᵐ[MeasureTheory.Measure.map (fun (ω : Ω) => (Z ω, X ω)) μ] (ProbabilityTheory.condDistrib Y (fun (ω : Ω) => (Z ω, X ω)) μ)
theorem ProbabilityTheory.condDistrib_eq_prod_of_indepFun {Ω : Type u_1} {S : Type u_2} {T : Type u_3} {U : Type u_4} [mΩ : MeasurableSpace Ω] [Countable S] [MeasurableSpace S] [DiscreteMeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass T] [Countable U] [DiscreteMeasurableSpace U] {X : ΩS} {Y : ΩT} {Z : ΩU} [Countable T] [Nonempty T] {V : Type u_5} [Countable V] [MeasurableSpace V] [MeasurableSingletonClass V] {W : ΩV} [Nonempty S] (hX : Measurable X) (hZ : Measurable Z) (hY : Measurable Y) (hW : Measurable W) (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsProbabilityMeasure μ] (h : ProbabilityTheory.IndepFun (fun (ω : Ω) => (X ω, Z ω)) (fun (ω : Ω) => (Y ω, W ω)) μ) :
(ProbabilityTheory.condDistrib (fun (ω : Ω) => (X ω, Y ω)) (fun (ω : Ω) => (Z ω, W ω)) μ) =ᵐ[MeasureTheory.Measure.map (fun (ω : Ω) => (Z ω, W ω)) μ] ((ProbabilityTheory.Kernel.prodMkRight V (ProbabilityTheory.condDistrib X Z μ)).prod (ProbabilityTheory.Kernel.prodMkLeft U (ProbabilityTheory.condDistrib Y W μ)))
theorem MeasureTheory.Measure.ae_of_compProd_eq_zero {α : Type u_6} {β : Type u_7} {mα : MeasurableSpace α} {mβ : MeasurableSpace β} {μ : MeasureTheory.Measure α} [MeasureTheory.SFinite μ] {κ : ProbabilityTheory.Kernel α β} [ProbabilityTheory.IsSFiniteKernel κ] {s : Set (α × β)} (hs : (μ.compProd κ) s = 0) :
∀ᵐ (a : α) ∂μ, (κ a) (Prod.mk a ⁻¹' s) = 0
theorem MeasureTheory.Measure.ae_of_ae_compProd {α : Type u_6} {β : Type u_7} {mα : MeasurableSpace α} {mβ : MeasurableSpace β} {μ : MeasureTheory.Measure α} [MeasureTheory.SFinite μ] {κ : ProbabilityTheory.Kernel α β} [ProbabilityTheory.IsSFiniteKernel κ] {p : α × βProp} (hp : ∀ᵐ (x : α × β) ∂μ.compProd κ, p x) :
∀ᵐ (a : α) ∂μ, ∀ᵐ (b : β) ∂κ a, p (a, b)
theorem ProbabilityTheory.Kernel.compProd_congr {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] {μ : MeasureTheory.Measure T} [MeasureTheory.SFinite μ] {κ κ' : ProbabilityTheory.Kernel T S} [ProbabilityTheory.IsSFiniteKernel κ] [ProbabilityTheory.IsSFiniteKernel κ'] {η η' : ProbabilityTheory.Kernel (T × S) U} [ProbabilityTheory.IsSFiniteKernel η] [ProbabilityTheory.IsSFiniteKernel η'] (hκ : κ =ᵐ[μ] κ') (hη : η =ᵐ[μ.compProd κ] η') :
(κ.compProd η) =ᵐ[μ] (κ'.compProd η')

The analogue of FiniteSupport for probability kernels.

Equations
  • κ.FiniteKernelSupport = ∀ (t : T), ∃ (A : Finset S), (κ t) (↑A) = 0
Instances For

    A kernel κ has almost everywhere finite support wrt a measure μ if, for almost every point t, then κ t has finite support. Note that we don't require any uniformity wrt t.

    Equations
    • κ.AEFiniteKernelSupport μ = ∀ᵐ (t : T) ∂μ, ∃ (A : Finset S), (κ t) (↑A) = 0
    Instances For
      theorem ProbabilityTheory.Kernel.FiniteKernelSupport.aefiniteKernelSupport {S : Type u_2} {T : Type u_3} [MeasurableSpace S] [MeasurableSpace T] {κ : ProbabilityTheory.Kernel T S} (hκ : κ.FiniteKernelSupport) (μ : MeasureTheory.Measure T) :
      κ.AEFiniteKernelSupport μ

      The definition doesn't use , but we keep it here still as it doesn't give anything interesting otherwise.

      Equations
      Instances For
        @[simp]
        theorem ProbabilityTheory.Kernel.AEFiniteKernelSupport.ae_eq_mk {S : Type u_2} {T : Type u_3} [MeasurableSpace S] [MeasurableSpace T] [Countable T] [MeasurableSingletonClass T] {μ : MeasureTheory.Measure T} {κ : ProbabilityTheory.Kernel T S} (hκ : κ.AEFiniteKernelSupport μ) :
        κ =ᵐ[μ] .mk
        theorem ProbabilityTheory.Kernel.aefiniteKernelSupport_iff {S : Type u_2} {T : Type u_3} [MeasurableSpace S] [MeasurableSpace T] [Countable T] [MeasurableSingletonClass T] [MeasurableSingletonClass S] {κ : ProbabilityTheory.Kernel T S} {μ : MeasureTheory.Measure T} :
        κ.AEFiniteKernelSupport μ ∃ (κ' : ProbabilityTheory.Kernel T S), κ'.FiniteKernelSupport κ' =ᵐ[μ] κ
        theorem ProbabilityTheory.Kernel.local_support_of_finiteKernelSupport {S : Type u_2} {T : Type u_3} [MeasurableSpace S] [MeasurableSpace T] {κ : ProbabilityTheory.Kernel T S} (h : κ.FiniteKernelSupport) (A : Finset T) :
        ∃ (B : Finset S), tA, (κ t) (↑B) = 0

        Finite kernel support locally implies uniform finite kernel support.

        Finite range implies finite kernel support.

        Deterministic kernels have finite kernel support.

        theorem ProbabilityTheory.Kernel.FiniteKernelSupport.map {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass U] {κ : ProbabilityTheory.Kernel T S} (hκ : κ.FiniteKernelSupport) (f : SU) :
        (κ.map f).FiniteKernelSupport

        maps preserve finite kernel support.

        theorem ProbabilityTheory.Kernel.AEFiniteKernelSupport.map {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass U] {κ : ProbabilityTheory.Kernel T S} {μ : MeasureTheory.Measure T} (hκ : κ.AEFiniteKernelSupport μ) {f : SU} :
        (κ.map f).AEFiniteKernelSupport μ
        theorem ProbabilityTheory.Kernel.FiniteKernelSupport.comap {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] {κ : ProbabilityTheory.Kernel T S} (hκ : κ.FiniteKernelSupport) {f : UT} (hf : Measurable f) :
        (κ.comap f hf).FiniteKernelSupport

        comaps preserve finite kernel support.

        theorem ProbabilityTheory.Kernel.AEFiniteKernelSupport.comap_equiv {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [Countable U] [MeasurableSingletonClass U] {κ : ProbabilityTheory.Kernel T S} {μ : MeasureTheory.Measure T} (hκ : κ.AEFiniteKernelSupport μ) (f : U ≃ᵐ T) :
        (κ.comap f ).AEFiniteKernelSupport (MeasureTheory.Measure.comap (⇑f) μ)
        theorem ProbabilityTheory.Kernel.FiniteKernelSupport.fst {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass S] {κ : ProbabilityTheory.Kernel T (S × U)} (hκ : κ.FiniteKernelSupport) :
        κ.fst.FiniteKernelSupport

        Projecting a kernel to first coordinate preserves finite kernel support.

        theorem ProbabilityTheory.Kernel.AEFiniteKernelSupport.fst {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass S] {κ : ProbabilityTheory.Kernel T (S × U)} {μ : MeasureTheory.Measure T} (hκ : κ.AEFiniteKernelSupport μ) :
        κ.fst.AEFiniteKernelSupport μ
        theorem ProbabilityTheory.Kernel.FiniteKernelSupport.snd {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass U] {κ : ProbabilityTheory.Kernel T (S × U)} (hκ : κ.FiniteKernelSupport) :
        κ.snd.FiniteKernelSupport

        Projecting a kernel to second coordinate preserves finite kernel support.

        theorem ProbabilityTheory.Kernel.AEFiniteKernelSupport.snd {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass U] {κ : ProbabilityTheory.Kernel T (S × U)} {μ : MeasureTheory.Measure T} (hκ : κ.AEFiniteKernelSupport μ) :
        κ.snd.AEFiniteKernelSupport μ
        theorem ProbabilityTheory.Kernel.aefiniteKernelSupport_of_cond {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] {κ : ProbabilityTheory.Kernel T (S × U)} [hU : Nonempty U] [MeasurableSingletonClass S] [MeasurableSingletonClass T] [MeasurableSingletonClass U] [Countable U] [Countable S] [Countable T] (μ : MeasureTheory.Measure T) [MeasureTheory.IsFiniteMeasure μ] (hκ : κ.AEFiniteKernelSupport μ) [ProbabilityTheory.IsFiniteKernel κ] :
        κ.condKernel.AEFiniteKernelSupport (μ.compProd κ.fst)

        Conditioning a kernel preserves finite kernel support.

        theorem ProbabilityTheory.Kernel.FiniteKernelSupport.swapRight {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass S] [MeasurableSingletonClass U] {κ : ProbabilityTheory.Kernel T (S × U)} (hκ : κ.FiniteKernelSupport) :
        κ.swapRight.FiniteKernelSupport

        Swapping a kernel right preserves finite kernel support.

        theorem ProbabilityTheory.Kernel.AEFiniteKernelSupport.swapRight {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] {κ : ProbabilityTheory.Kernel T (S × U)} {μ : MeasureTheory.Measure T} [MeasurableSingletonClass S] [MeasurableSingletonClass U] (hκ : κ.AEFiniteKernelSupport μ) :
        κ.swapRight.AEFiniteKernelSupport μ
        theorem ProbabilityTheory.Kernel.FiniteKernelSupport.prod {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] {κ : ProbabilityTheory.Kernel T S} {η : ProbabilityTheory.Kernel T U} [MeasurableSingletonClass S] [MeasurableSingletonClass U] [ProbabilityTheory.IsMarkovKernel κ] [ProbabilityTheory.IsMarkovKernel η] (hκ : κ.FiniteKernelSupport) (hη : η.FiniteKernelSupport) :
        (κ.prod η).FiniteKernelSupport

        Products preserve finite kernel support.

        theorem ProbabilityTheory.Kernel.AEFiniteKernelSupport.prod {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] {κ : ProbabilityTheory.Kernel T S} {η : ProbabilityTheory.Kernel T U} [ProbabilityTheory.IsMarkovKernel κ] [ProbabilityTheory.IsMarkovKernel η] {μ : MeasureTheory.Measure T} (hκ : κ.AEFiniteKernelSupport μ) (hη : η.AEFiniteKernelSupport μ) :
        (κ.prod η).AEFiniteKernelSupport μ
        theorem ProbabilityTheory.Kernel.FiniteKernelSupport.compProd {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [MeasurableSingletonClass S] [MeasurableSingletonClass U] {κ : ProbabilityTheory.Kernel T S} {η : ProbabilityTheory.Kernel (T × S) U} (hκ : κ.FiniteKernelSupport) (hη : η.FiniteKernelSupport) :
        (κ.compProd η).FiniteKernelSupport

        Composition-product preserves finite kernel support

        theorem ProbabilityTheory.Kernel.AEFiniteKernelSupport.compProd {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] [Countable S] [MeasurableSingletonClass S] [Countable T] [MeasurableSingletonClass T] [MeasurableSingletonClass U] {κ : ProbabilityTheory.Kernel T S} {η : ProbabilityTheory.Kernel (T × S) U} {μ : MeasureTheory.Measure T} [MeasureTheory.SFinite μ] (hκ : κ.AEFiniteKernelSupport μ) (hη : η.AEFiniteKernelSupport (μ.compProd κ)) :
        (κ.compProd η).AEFiniteKernelSupport μ
        theorem ProbabilityTheory.Kernel.FiniteKernelSupport.prodMkRight {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] {κ : ProbabilityTheory.Kernel T S} (hκ : κ.FiniteKernelSupport) :
        (ProbabilityTheory.Kernel.prodMkRight U κ).FiniteKernelSupport

        prodMkRight preserves finite kernel support.

        theorem ProbabilityTheory.Kernel.FiniteKernelSupport.prodMkLeft {S : Type u_2} {T : Type u_3} {U : Type u_4} [MeasurableSpace S] [MeasurableSpace T] [MeasurableSpace U] {κ : ProbabilityTheory.Kernel T S} (hκ : κ.FiniteKernelSupport) :
        (ProbabilityTheory.Kernel.prodMkLeft U κ).FiniteKernelSupport

        prodMkLeft preserves finite kernel support.