Documentation

Atlas.TheoryOfProbability.code.LargeDeviations

structure IsRateFunction {X : Type u_1} [TopologicalSpace X] (I : XENNReal) :

A rate function I : X → [0, ∞] is, by definition, a lower-semicontinuous function. This is the basic regularity hypothesis used in the formulation of a large deviation principle.

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    structure IsGoodRateFunction {X : Type u_1} [TopologicalSpace X] (I : XENNReal) extends IsRateFunction I :

    A good rate function is a rate function whose sub-level sets {x | I x ≤ a} are all compact. Goodness ensures that the variational problems inf_{x ∈ Γ} I(x) are attained.

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      structure IsConvexRateFunction {X : Type u_1} [TopologicalSpace X] [AddCommMonoid X] [Module X] (I : XENNReal) extends IsRateFunction I :

      A convex rate function on a real vector space is a rate function I that is convex: I(ax + by) ≤ a · I(x) + b · I(y) for all x, y ∈ X and all weights a, b ≥ 0 with a + b = 1.

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        structure SatisfiesLDP {X : Type u_1} [TopologicalSpace X] [MeasurableSpace X] (μ : MeasureTheory.Measure X) (I : XENNReal) :

        A sequence of measures μ : ℕ → Measure X satisfies the large deviation principle with rate function I : X → [0, ∞] and speed n if I is a rate function and the following asymptotic bounds hold for every Borel set Γ ⊆ X: -inf_{x ∈ Γ°} I(x) ≤ liminf (1/n) log μ_n(Γ) ≤ limsup (1/n) log μ_n(Γ) ≤ -inf_{x ∈ Γ̄} I(x). Concretely, this is encoded as the standard pair of bounds: a liminf lower bound over open sets U and a limsup upper bound over closed sets F.

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