Documentation

PFR.Mathlib.Probability.Kernel.Composition.Comp

theorem ProbabilityTheory.Kernel.map_map {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α β) {f : βγ} (hf : Measurable f) {g : γδ} (hg : Measurable g) :
(κ.map f).map g = κ.map (g f)
theorem ProbabilityTheory.Kernel.map_swapRight {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ)) {f : γ × βδ} :
noncomputable def ProbabilityTheory.Kernel.deleteMiddle {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
Kernel α (β × δ)

Given a kernel taking values in a product of three spaces, forget the middle one.

Equations
Instances For
    theorem ProbabilityTheory.Kernel.deleteMiddle_eq {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
    κ.deleteMiddle = κ.map fun (p : β × γ × δ) => (p.1, p.2.2)
    instance ProbabilityTheory.Kernel.instIsMarkovKernelProdDeleteMiddle {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) [IsMarkovKernel κ] :
    instance ProbabilityTheory.Kernel.instIsZeroOrMarkovKernelProdDeleteMiddle {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) [IsZeroOrMarkovKernel κ] :
    @[simp]
    theorem ProbabilityTheory.Kernel.fst_deleteMiddle {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
    @[simp]
    theorem ProbabilityTheory.Kernel.snd_deleteMiddle {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
    @[simp]
    theorem ProbabilityTheory.Kernel.deleteMiddle_zero {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] :
    @[simp]
    theorem ProbabilityTheory.Kernel.deleteMiddle_map_prod {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {ε : Type u_5} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} {x✝³ : MeasurableSpace ε} [MeasurableSpace γ] (κ : Kernel α β) {f : βγ} {g : βδ} {g' : βε} (hg : Measurable g) :
    (κ.map fun (b : β) => (f b, g b, g' b)).deleteMiddle = κ.map fun (b : β) => (f b, g' b)
    @[simp]
    theorem ProbabilityTheory.Kernel.deleteMiddle_compProd {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (ξ : Kernel α β) [IsSFiniteKernel ξ] (κ : Kernel (α × β) (γ × δ)) [IsSFiniteKernel κ] :
    noncomputable def ProbabilityTheory.Kernel.deleteRight {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
    Kernel α (β × γ)

    Given a kernel taking values in a product of three spaces, forget the last variable.

    Equations
    Instances For
      theorem ProbabilityTheory.Kernel.deleteRight_eq {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
      κ.deleteRight = κ.map fun (p : β × γ × δ) => (p.1, p.2.1)
      @[simp]
      theorem ProbabilityTheory.Kernel.deleteRight_zero {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] :
      instance ProbabilityTheory.Kernel.instIsMarkovKernelProdDeleteRight {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) [IsMarkovKernel κ] :
      instance ProbabilityTheory.Kernel.instIsZeroOrMarkovKernelProdDeleteRight {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) [IsZeroOrMarkovKernel κ] :
      @[simp]
      theorem ProbabilityTheory.Kernel.fst_deleteRight {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
      @[simp]
      theorem ProbabilityTheory.Kernel.snd_deleteRight {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
      @[simp]
      theorem ProbabilityTheory.Kernel.deleteRight_map_prod {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {ε : Type u_5} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} {x✝³ : MeasurableSpace ε} [MeasurableSpace γ] (κ : Kernel α β) {f : βγ} {g : βδ} {g' : βε} (hg' : Measurable g') :
      (κ.map fun (b : β) => (f b, g b, g' b)).deleteRight = κ.map fun (b : β) => (f b, g b)
      noncomputable def ProbabilityTheory.Kernel.reverse {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
      Kernel α (δ × γ × β)

      Given a kernel taking values in a product of three spaces, reverse the order of the spaces.

      Equations
      Instances For
        theorem ProbabilityTheory.Kernel.reverse_eq {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
        κ.reverse = κ.map fun (p : β × γ × δ) => (p.2.2, p.2.1, p.1)
        theorem ProbabilityTheory.Kernel.reverse_zero {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] :
        @[simp]
        theorem ProbabilityTheory.Kernel.reverse_reverse {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
        instance ProbabilityTheory.Kernel.instIsMarkovKernelProdReverse {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) [IsMarkovKernel κ] :
        instance ProbabilityTheory.Kernel.instIsZeroOrMarkovKernelProdReverse {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) [IsZeroOrMarkovKernel κ] :
        @[simp]
        theorem ProbabilityTheory.Kernel.swapRight_deleteMiddle_reverse {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
        @[simp]
        theorem ProbabilityTheory.Kernel.swapRight_snd_reverse {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :
        @[simp]
        theorem ProbabilityTheory.Kernel.swapRight_deleteRight_reverse {α : Type u_1} {β : Type u_2} {γ : Type u_3} {δ : Type u_4} {x✝ : MeasurableSpace α} {x✝¹ : MeasurableSpace β} {x✝² : MeasurableSpace δ} [MeasurableSpace γ] (κ : Kernel α (β × γ × δ)) :

        Reversing preserves finite kernel support