Adaptive estimation of the stationary density of a stochastic differential equation driven by a fractional Brownian motion

被引：0

作者：

Karine Bertin

Nicolas Klutchnikoff

Fabien Panloup

Maylis Varvenne

机构：

[1] Universidad de Valparaiso,CIMFAV

[2] Univ Rennes,INGEMAT

[3] CNRS,Laboratoire angevin de recherche en mathématiques (LAREMA)

[4] IRMAR – UMR 6625,Institut de Mathématiques de Toulouse (IMT)

[5] Université d’Angers,undefined

[6] CNRS,undefined

[7] Université de Toulouse 1 Capitole,undefined

[8] 2 Rue du Doyen-Gabriel-Marty,undefined

来源：

Statistical Inference for Stochastic Processes | 2020年 / 23卷

关键词：

Fractional Brownian motion; Non-parametric fractional diffusion model; Stationary density; Rate of convergence; Adaptive density estimation; 62G07; 60G22; 60H10; 62M09;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

We build and study a data-driven procedure for the estimation of the stationary density f of an additive fractional SDE. To this end, we also prove some new concentrations bounds for discrete observations of such dynamics in stationary regime.

引用

页码：271 / 300

页数：29

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