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 #

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_2} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] {ε₁ : ENNReal} {ε₂ : ENNReal} (μ : MeasureTheory.Measure Ω) (ν : MeasureTheory.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_2} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] (μ : MeasureTheory.Measure Ω) (ν : MeasureTheory.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_2} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] (μ : MeasureTheory.Measure Ω) (ν : MeasureTheory.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.

    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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      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.

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        The "identity" equivalence between the type synonym LevyProkhorov α and α.

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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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          theorem MeasureTheory.measure_eq_measure_of_levyProkhorovEDist_eq_zero_of_isClosed {Ω : Type u_2} [MeasurableSpace Ω] [PseudoEMetricSpace Ω] [OpensMeasurableSpace Ω] {μ : MeasureTheory.Measure Ω} {ν : MeasureTheory.Measure Ω} (hLP : MeasureTheory.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.

          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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          If Ω is a Borel space, then the Lévy-Prokhorov distance levyProkhorovDist makes ProbabilityMeasure Ω 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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          • MeasureTheory.levyProkhorovDist_metricSpace_probabilityMeasure = MetricSpace.mk

          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.

          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.

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

          theorem MeasureTheory.BoundedContinuousFunction.integral_eq_integral_meas_le_of_hasFiniteIntegral {α : Type u_3} [MeasurableSpace α] [TopologicalSpace α] [OpensMeasurableSpace α] (f : BoundedContinuousFunction α ) (μ : MeasureTheory.Measure α) (f_nn : 0 ≤ᵐ[μ] f) (hf : MeasureTheory.HasFiniteIntegral (⇑f) μ) :
          ∫ (ω : α), f ωμ = ∫ (t : ) in Set.Ioc 0 f, (μ {a : α | t f a}).toReal

          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.

          theorem MeasureTheory.BoundedContinuousFunction.integral_eq_integral_meas_le {α : Type u_3} [MeasurableSpace α] [TopologicalSpace α] [OpensMeasurableSpace α] (f : BoundedContinuousFunction α ) (μ : MeasureTheory.Measure α) [MeasureTheory.IsFiniteMeasure μ] (f_nn : 0 ≤ᵐ[μ] f) :
          ∫ (ω : α), f ωμ = ∫ (t : ) in Set.Ioc 0 f, (μ {a : α | t f a}).toReal

          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.

          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_2} [MeasurableSpace Ω] [PseudoMetricSpace Ω] [OpensMeasurableSpace Ω] (f : BoundedContinuousFunction Ω ) {A : Set } (A_finmeas : MeasureTheory.volume A ) (μ : MeasureTheory.ProbabilityMeasure Ω) :
          Filter.Tendsto (fun (ε : ) => ∫ (t : ) in A, (↑(μ (Metric.thickening ε {a : Ω | t f a}))).toReal) (nhdsWithin 0 (Set.Ioi 0)) (nhds (∫ (t : ) in A, (↑(μ {a : Ω | t f a})).toReal))

          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 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.SeparableSpace.exists_measurable_partition_diam_le (Ω : Type u_2) [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.

          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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