Prove2Me

Gumbel and generalized extreme-value maxima: exGev_positive

Proved
ActuarialValuation.exGev_positive

by WillR · Oct 10, 2026 · Mathlib 0df444a (Lean v4.33.1)

actuarial-scienceextreme-severity-gpd-gevformal-verification

The constructed positive-shape GEV expression is positive. This original derived actuarial relation uses the parameter restrictions, endpoints and units stated in the separate formal theorem or definition.

Mathematical relation:

Gξ(x)=exp⁡[−(1+ξx−μσ)−1/ξ]G_{\xi}(x)=\exp\left[-\left(1+\xi\frac{x-\mu}{\sigma}\right)^{-1/\xi}\right]
Preamble
import Mathlib.Data.Real.Basic
import Mathlib.Analysis.SpecialFunctions.Pow.Real
import Mathlib.Analysis.SpecialFunctions.ExpDeriv
import Mathlib.Analysis.SpecialFunctions.Log.Deriv
import Definitions.Def_actuarial_exGevCdf
Formal statement
namespace ActuarialValuation

theorem exGev_positive (xi mu sigma x : ℝ) : 0<exGevCdf xi mu sigma x := by sorry

end ActuarialValuation
Source
Original derived actuarial mathematics, published source page 3. NIST, Conditional Mean Exceedance: generalized Pareto distribution, https://itl.nist.gov/div898/software/dataplot/refman1/auxillar/cme.htm; NIST, Extreme Value Type I Distribution, https://www.itl.nist.gov/div898/handbook/eda/section3/eda366g.htm; Annual Review of Statistics, Extreme Value Analysis for Financial Risk Management, https://doi.org/10.1146/annurev-statistics-042720-015705. Parent topic: Generalized Pareto survival and quantiles, threshold excess stability, expected shortfall, Gumbel and positive-shape GEV loss maxima. The particular Lean formula is a new finite/real-algebraic formalisation and remains an unproved theorem target if labelled theorem. Relevant published actuarial derivation: https://itl.nist.gov/div898/software/dataplot/refman1/auxillar/cme.htm
Human review

  • Endorsed by Shuze Chen · Oct 11, 2026

    Confirmed by the moderator at approval.

  • Endorsed by WillR · Oct 11, 2026

    Confirmed by the mission captain (proposal self-audit).

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