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

Karine Bertin (), Nicolas Klutchnikoff (), Fabien Panloup () and Maylis Varvenne ()
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Karine Bertin: Universidad de Valparaiso
Nicolas Klutchnikoff: Univ Rennes, CNRS, IRMAR – UMR 6625
Fabien Panloup: Université d’Angers, CNRS
Maylis Varvenne: Université de Toulouse 1 Capitole, 2 Rue du Doyen-Gabriel-Marty

Statistical Inference for Stochastic Processes, 2020, vol. 23, issue 2, No 3, 300 pages

Abstract: Abstract 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.

Keywords: Fractional Brownian motion; Non-parametric fractional diffusion model; Stationary density; Rate of convergence; Adaptive density estimation; 62G07; 60G22; 60H10; 62M09 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11203-020-09218-0

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