Documentation

Mathlib.MeasureTheory.Measure.LevyProkhorovMetric

The Lévy-Prokhorov distance on spaces of finite measures and probability measures #

Main definitions #

Main results #

Tags #

finite measure, probability measure, weak convergence, convergence in distribution, metrizability

Lévy-Prokhorov metric #

noncomputable def MeasureTheory.levyProkhorovEDist {Ω : Type u_1} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] (μ ν : Measure Ω) :

The Lévy-Prokhorov edistance between measures: d(μ,ν) = inf {r ≥ 0 | ∀ B, μ B ≤ ν Bᵣ + r ∧ ν B ≤ μ Bᵣ + r}.

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    theorem MeasureTheory.meas_le_of_le_of_forall_le_meas_thickening_add {Ω : Type u_1} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] {ε₁ ε₂ : ENNReal} (μ ν : Measure Ω) (h_le : ε₁ ε₂) {B : Set Ω} (hε₁ : μ B ν (Metric.thickening ε₁.toReal B) + ε₁) :
    μ B ν (Metric.thickening ε₂.toReal B) + ε₂
    theorem MeasureTheory.levyProkhorovEDist_le_of_forall_add_pos_le {Ω : Type u_1} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] (μ ν : Measure Ω) (δ : ENNReal) (h : ∀ (ε : ENNReal) (B : Set Ω), 0 < εε < MeasurableSet Bμ B ν (Metric.thickening (δ + ε).toReal B) + δ + ε ν B μ (Metric.thickening (δ + ε).toReal B) + δ + ε) :

    A general sufficient condition for bounding levyProkhorovEDist from above.

    theorem MeasureTheory.levyProkhorovEDist_le_of_forall {Ω : Type u_1} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] (μ ν : Measure Ω) (δ : ENNReal) (h : ∀ (ε : ENNReal) (B : Set Ω), δ < εε < MeasurableSet Bμ B ν (Metric.thickening ε.toReal B) + ε ν B μ (Metric.thickening ε.toReal B) + ε) :

    A simple general sufficient condition for bounding levyProkhorovEDist from above.

    noncomputable def MeasureTheory.levyProkhorovDist {Ω : Type u_1} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] (μ ν : Measure Ω) :

    The Lévy-Prokhorov distance between finite measures: d(μ,ν) = inf {r ≥ 0 | ∀ B, μ B ≤ ν Bᵣ + r ∧ ν B ≤ μ Bᵣ + r}.

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      theorem MeasureTheory.measure_le_measure_closure_of_levyProkhorovEDist_eq_zero {Ω : Type u_1} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] [OpensMeasurableSpace Ω] {μ ν : Measure Ω} (hLP : levyProkhorovEDist μ ν = 0) {s : Set Ω} (s_mble : MeasurableSet s) (h_finite : δ > 0, ν (Metric.thickening δ s) ) :
      μ s ν (closure s)
      theorem MeasureTheory.measure_eq_measure_of_levyProkhorovEDist_eq_zero_of_isClosed {Ω : Type u_1} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] [OpensMeasurableSpace Ω] {μ ν : Measure Ω} (hLP : levyProkhorovEDist μ ν = 0) {s : Set Ω} (s_closed : IsClosed s) (hμs : δ > 0, μ (Metric.thickening δ s) ) (hνs : δ > 0, ν (Metric.thickening δ s) ) :
      μ s = ν s

      Two measures at vanishing Lévy-Prokhorov distance from each other assign the same values to all closed sets.

      theorem MeasureTheory.levyProkhorovEDist_le_of_forall_le {Ω : Type u_1} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] [OpensMeasurableSpace Ω] (μ ν : Measure Ω) [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] (δ : ENNReal) (h : ∀ (ε : ENNReal) (B : Set Ω), δ < εε < MeasurableSet Bμ B ν (Metric.thickening ε.toReal B) + ε) :

      A simple sufficient condition for bounding levyProkhorovEDist between probability measures from above. The condition involves only one of two natural bounds, the other bound is for free.

      theorem MeasureTheory.levyProkhorovDist_le_of_forall_le {Ω : Type u_1} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] [OpensMeasurableSpace Ω] (μ ν : Measure Ω) [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] {δ : } (δ_nn : 0 δ) (h : ∀ (ε : ) (B : Set Ω), δ < εMeasurableSet Bμ B ν (Metric.thickening ε B) + ENNReal.ofReal ε) :

      A simple sufficient condition for bounding levyProkhorovDist between probability measures from above. The condition involves only one of two natural bounds, the other bound is for free.

      Equipping measures with the Lévy-Prokhorov metric #

      structure MeasureTheory.LevyProkhorov (α : Type u_2) :
      Type u_2

      A type synonym, to be used for Measure α, FiniteMeasure α, or ProbabilityMeasure α, when they are to be equipped with the Lévy-Prokhorov distance.

      • ofMeasure :: (
        • toMeasure : α

          Turn an element of the space of measure equipped with the Lévy-Prokhorov metric into the corresponding measure.

      • )
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        @[simp]
        theorem MeasureTheory.LevyProkhorov.toMeasureEquiv_symm_apply_toMeasure {α : Type u_2} (toMeasure : α) :
        (toMeasureEquiv.symm toMeasure).toMeasure = toMeasure
        @[deprecated MeasureTheory.LevyProkhorov.toMeasureEquiv (since := "2025-10-28")]

        Alias of MeasureTheory.LevyProkhorov.toMeasureEquiv.


        LevyProkhorov.toMeasure as an equiv.

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          The Lévy-Prokhorov distance levyProkhorovEDist makes Measure Ω a pseudoemetric space. The instance is recorded on the type synonym LevyProkhorov (Measure Ω) := Measure Ω.

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          The Lévy-Prokhorov distance levyProkhorovDist makes FiniteMeasure Ω a pseudometric space. The instance is recorded on the type synonym LevyProkhorov (FiniteMeasure Ω) := FiniteMeasure Ω.

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          The Lévy-Prokhorov distance levyProkhorovDist makes ProbabilityMeasure Ω a pseudometric space. The instance is recorded on the type synonym LevyProkhorov (ProbabilityMeasure Ω) := ProbabilityMeasure Ω.

          Note: For this pseudometric to give the topology of convergence in distribution, one must furthermore assume that Ω is separable.

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          @[deprecated MeasureTheory.LevyProkhorov.dist_probabilityMeasure_def (since := "2025-10-28")]

          Alias of MeasureTheory.LevyProkhorov.dist_probabilityMeasure_def.

          If Ω is a Borel space, then the Lévy-Prokhorov distance levyProkhorovDist makes ProbabilityMeasure Ω into a metric space. The instance is recorded on the type synonym LevyProkhorov (ProbabilityMeasure Ω) := ProbabilityMeasure Ω.

          Note: For this metric to give the topology of convergence in distribution, one must furthermore assume that Ω is separable.

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          The Lévy-Prokhorov topology is at least as fine as convergence in distribution #

          A version of the layer cake formula for bounded continuous functions which have finite integral: ∫ f dμ = ∫ t in (0, ‖f‖], μ {x | f(x) ≥ t} dt.

          A version of the layer cake formula for bounded continuous functions and finite measures: ∫ f dμ = ∫ t in (0, ‖f‖], μ {x | f(x) ≥ t} dt.

          theorem MeasureTheory.BoundedContinuousFunction.integral_le_of_levyProkhorovEDist_lt {Ω : Type u_1} [MeasurableSpace Ω] [PseudoMetricSpace Ω] [OpensMeasurableSpace Ω] (μ ν : Measure Ω) [IsFiniteMeasure μ] [IsFiniteMeasure ν] {ε : } (ε_pos : 0 < ε) (hμν : levyProkhorovEDist μ ν < ENNReal.ofReal ε) (f : BoundedContinuousFunction Ω ) (f_nn : 0 ≤ᶠ[ae μ] f) :
          (ω : Ω), f ω μ ( (t : ) in Set.Ioc 0 f, ν.real (Metric.thickening ε {a : Ω | t f a})) + ε * f

          Assuming levyProkhorovEDist μ ν < ε, we can bound ∫ f ∂μ in terms of ∫ t in (0, ‖f‖], ν (thickening ε {x | f(x) ≥ t}) dt and ‖f‖.

          theorem MeasureTheory.tendsto_integral_meas_thickening_le {Ω : Type u_1} [MeasurableSpace Ω] [PseudoMetricSpace Ω] [OpensMeasurableSpace Ω] (f : BoundedContinuousFunction Ω ) {A : Set } (A_finmeas : volume A ) (μ : ProbabilityMeasure Ω) :
          Filter.Tendsto (fun (ε : ) => (t : ) in A, (↑μ).real (Metric.thickening ε {a : Ω | t f a})) (nhdsWithin 0 (Set.Ioi 0)) (nhds ( (t : ) in A, (↑μ).real {a : Ω | t f a}))

          A monotone decreasing convergence lemma for integrals of measures of thickenings: ∫ t in (0, ‖f‖], μ (thickening ε {x | f(x) ≥ t}) dt tends to ∫ t in (0, ‖f‖], μ {x | f(x) ≥ t} dt as ε → 0.

          The identity map LevyProkhorov (ProbabilityMeasure Ω) → ProbabilityMeasure Ω is continuous.

          @[deprecated MeasureTheory.LevyProkhorov.continuous_toMeasure_probabilityMeasure (since := "2025-10-28")]

          Alias of MeasureTheory.LevyProkhorov.continuous_toMeasure_probabilityMeasure.


          The identity map LevyProkhorov (ProbabilityMeasure Ω) → ProbabilityMeasure Ω is continuous.

          The topology of the Lévy-Prokhorov metric is at least as fine as the topology of convergence in distribution.

          @[deprecated MeasureTheory.LevyProkhorov.le_convergenceInDistribution (since := "2025-10-28")]

          Alias of MeasureTheory.LevyProkhorov.le_convergenceInDistribution.


          The topology of the Lévy-Prokhorov metric is at least as fine as the topology of convergence in distribution.

          On separable spaces the Lévy-Prokhorov distance metrizes convergence in distribution #

          theorem MeasureTheory.ProbabilityMeasure.toMeasure_add_pos_gt_mem_nhds {Ω : Type u_1} [PseudoMetricSpace Ω] [MeasurableSpace Ω] [OpensMeasurableSpace Ω] (P : ProbabilityMeasure Ω) {G : Set Ω} (G_open : IsOpen G) {ε : ENNReal} (ε_pos : 0 < ε) :
          {Q : ProbabilityMeasure Ω | P G < Q G + ε} nhds P
          theorem MeasureTheory.SeparableSpace.exists_measurable_partition_diam_le (Ω : Type u_1) [PseudoMetricSpace Ω] [MeasurableSpace Ω] [OpensMeasurableSpace Ω] [TopologicalSpace.SeparableSpace Ω] {ε : } (ε_pos : 0 < ε) :
          ∃ (As : Set Ω), (∀ (n : ), MeasurableSet (As n)) (∀ (n : ), Bornology.IsBounded (As n)) (∀ (n : ), Metric.diam (As n) ε) ⋃ (n : ), As n = Set.univ Pairwise fun (n m : ) => Disjoint (As n) (As m)

          In a separable pseudometric space, for any ε > 0 there exists a countable collection of disjoint Borel measurable subsets of diameter at most ε that cover the whole space.

          The topology of the Lévy-Prokhorov metric on probability measures on a separable space coincides with the topology of convergence in distribution.

          @[deprecated MeasureTheory.LevyProkhorov.eq_convergenceInDistribution (since := "2025-10-28")]

          Alias of MeasureTheory.LevyProkhorov.eq_convergenceInDistribution.


          The topology of the Lévy-Prokhorov metric on probability measures on a separable space coincides with the topology of convergence in distribution.

          The identity map is a homeomorphism from ProbabilityMeasure Ω with the topology of convergence in distribution to ProbabilityMeasure Ω with the Lévy-Prokhorov (pseudo)metric.

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            @[deprecated MeasureTheory.LevyProkhorov.probabilityMeasureHomeomorph (since := "2025-10-28")]

            Alias of MeasureTheory.LevyProkhorov.probabilityMeasureHomeomorph.


            The identity map is a homeomorphism from ProbabilityMeasure Ω with the topology of convergence in distribution to ProbabilityMeasure Ω with the Lévy-Prokhorov (pseudo)metric.

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