LeanMachineLearning

ProbabilityTheory.Kernel.HasSubexponentialMGF🔗

Structure

From the authors

A random variable X has a sub-exponential moment-generating function with parameters (V, b) with respect to a kernel κ and a measure ν if for every t with b * |t| ≤ 1, exp (t * X) is integrable with respect to κ ∘ₘ ν and, for ν-almost all ω', the moment-generating function of X with respect to κ ω' is bounded by exp (V * t ^ 2 / 2). For b = 0 this is Kernel.HasSubgaussianMGF X V κ ν.

Types
  • Ω : Type u_1mΩ : MeasurableSpace ΩA measurable space is a space equipped with a σ-algebra.
  • Ω' : Type u_2mΩ' : MeasurableSpace Ω'
Given
  • X : Ω →
  • V :
  • b :
  • κ : Kernel Ω' ΩA kernel from a measurable space α to another measurable space β is a measurable function κ : α → Measure β.
  • ν : MeasureTheory.Measure Ω'A measure is defined to be an outer measure that is countably additive on measurable sets, with the additional assumption that the outer measure is the canonical extension of the restricted measure.
Result
Prop
Fields
  • integrable_exp_mul : ∀ (t : ), b * |t|1 → MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) (ν.bind ⇑κ)Integrable f μ means that f is measurable and that the integral ∫⁻ a, ‖f a‖ ∂μ is finite.
  • mgf_le : ∀ᵐ (ω' : Ω')ν, ∀ (t : ), b * |t|1 → mgf X (κ ω') tReal.exp (V * t ^ 2 / 2)f.Eventually p or ∀ᶠ x in f, p x mean that {x | p x} ∈ f.
Code
structure Kernel.HasSubexponentialMGF (X : Ω → ℝ) (V b : ℝ)
    (κ : Kernel Ω' Ω) (ν : Measure Ω' := by volume_tac) : Prop where
  integrable_exp_mul : ∀ t, b * |t| ≤ 1 → Integrable (fun ω ↦ exp (t * X ω)) (κ ∘ₘ ν)
  mgf_le : ∀ᵐ ω' ∂ν, ∀ t, b * |t| ≤ 1 → mgf X (κ ω') t ≤ exp (V * t ^ 2 / 2)

Meaning last changed in v4.34.0-rc2-76-g565f652 (2026-09-10).

Self-contained, with its dependencies inlined and proofs replaced by sorry: download the raw file · open it in the Lean web editor.

Dependency graph

Nothing to draw. Its statement rests on no other declaration in this project, and names nothing from a package left unaudited — so the graph is this declaration alone. That is the answer, not a missing picture.

Audit surface: 0 project declarations, 60 external constants

✓ Proved: no sorry anywhere in its closure

This is the tool's own reading of one build's recorded axioms, and it is not robust against an author who wants it to pass. Checking meant to be relied on should go through Comparator, which replays the proof through the kernel from an export against an explicit list of permitted axioms.