Rate of estimation for the stationary distribution of jump-processes over anisotropic holder classes

We study the problem of the non-parametric estimation for the density - of the stationary distribution of the multivariate stochastic differential equation with jumps (X), when the dimension d is such that d - 3. From the continuous observation of the sampling path on [0,T]we show that, under anisot...

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Detalles Bibliográficos
Autor: Amorino, Chiara
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/71772
Acceso en línea:http://hdl.handle.net/10230/71772
http://dx.doi.org/10.1214/21-EJS1913
Access Level:acceso abierto
Palabra clave:Convergence rate
Density estimation
Ergodic diffusion with jumps
Lévy driven SDE
Non-parametric statistics
Descripción
Sumario:We study the problem of the non-parametric estimation for the density - of the stationary distribution of the multivariate stochastic differential equation with jumps (X), when the dimension d is such that d - 3. From the continuous observation of the sampling path on [0,T]we show that, under anisotropic Hölder smoothness constraints, kernel based estimators can achieve fast convergence rates. In particular, they are as fast as the ones found by Dalalyan and Reiss [11] for the estimation of the invariant density in the case without jumps under isotropic Hölder smoothness constraints. Moreover, they are faster than the ones found by Strauch [32] for the invariant density estimation of continuous stochastic differential equations, under anisotropic Hölder smoothness constraints. Furthermore, we obtain a minimax lower bound on the L2-risk for pointwise estimation, with the same rate up to a log(T ) term. It implies that, on a class of diffusions whose invariant density belongs to the anisotropic Holder class we are considering, it is impossible to find an estimator with a rate of estimation faster than the one we propose.