Discrete-time inference for slow-fast systems driven by fractional Brownian motion

Autor:	Bourguin, Solesne, Gailus, Siragan, Spiliopoulos, Konstantinos
Rok vydání:	2020
Předmět:	Mathematics - Statistics Theory Mathematics - Dynamical Systems Mathematics - Probability 60G22 60H10 60H07 62F12
Druh dokumentu:	Working Paper
Popis:	We study statistical inference for small-noise-perturbed multiscale dynamical systems where the slow motion is driven by fractional Brownian motion. We develop statistical estimators for both the Hurst index as well as a vector of unknown parameters in the model based on a single time series of observations from the slow process only. We prove that these estimators are both consistent and asymptotically normal as the amplitude of the perturbation and the time-scale separation parameter go to zero. Numerical simulations illustrate the theoretical results. Comment: arXiv admin note: text overlap with arXiv:1906.02131
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2007.11665 Zobrazit plný text záznamu View this record from Arxiv