Extreme Value theory and Poisson statistics for discrete time samplings of stochastic differential equations

Fuente: arXiv
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Auteurs principaux: Flandoli, F., Galatolo, S., Giulietti, P., Vaienti, S.
Format: Preprint
Publié: 2023
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author Flandoli, F.
Galatolo, S.
Giulietti, P.
Vaienti, S.
author_facet Flandoli, F.
Galatolo, S.
Giulietti, P.
Vaienti, S.
contents We investigate the distribution and multiple occurrences of extreme events stochastic processes constructed by sampling the solution of a Stochastic Differential Equation on $\mathbb{R}^n$. We do so by studying the action of an annealead transfer operators on ad-hoc spaces of probability densities. The spectral properties of such operators are obtained by employing a mixture of techniques coming from SDE theory and a functional analytic approach to dynamical systems.
format Preprint
id arxiv_https___arxiv_org_abs_2310_13972
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Extreme Value theory and Poisson statistics for discrete time samplings of stochastic differential equations
Flandoli, F.
Galatolo, S.
Giulietti, P.
Vaienti, S.
Dynamical Systems
Probability
We investigate the distribution and multiple occurrences of extreme events stochastic processes constructed by sampling the solution of a Stochastic Differential Equation on $\mathbb{R}^n$. We do so by studying the action of an annealead transfer operators on ad-hoc spaces of probability densities. The spectral properties of such operators are obtained by employing a mixture of techniques coming from SDE theory and a functional analytic approach to dynamical systems.
title Extreme Value theory and Poisson statistics for discrete time samplings of stochastic differential equations
topic Dynamical Systems
Probability
url https://arxiv.org/abs/2310.13972