Dynamical large deviations of linear diffusions
J du Buisson, H Touchette - Physical Review E, 2023 - APS
Linear diffusions are used to model a large number of stochastic processes in physics,
including small mechanical and electrical systems perturbed by thermal noise, as well as …
including small mechanical and electrical systems perturbed by thermal noise, as well as …
Asymptotic behavior of the fractional Heston model
H Guennoun, A Jacquier, P Roome, F Shi - SIAM Journal on Financial …, 2018 - SIAM
We consider the fractional Heston model originally proposed by Comte, Coutin, and Renault
[Ann. Finance, 8 (2012), pp. 337--378]. Inspired by recent groundbreaking work on rough …
[Ann. Finance, 8 (2012), pp. 337--378]. Inspired by recent groundbreaking work on rough …
Anomalous scaling of dynamical large deviations
D Nickelsen, H Touchette - Physical review letters, 2018 - APS
The typical values and fluctuations of time-integrated observables of nonequilibrium
processes driven in steady states are known to be characterized by large deviation …
processes driven in steady states are known to be characterized by large deviation …
Dynamical large deviations of diffusions
J Buisson - arXiv preprint arXiv:2210.09040, 2022 - arxiv.org
We solve two problems related to the fluctuations of time-integrated functionals of Markov
diffusions, used in physics to model nonequilibrium systems. In the first we derive and …
diffusions, used in physics to model nonequilibrium systems. In the first we derive and …
Neyman-pearson detection of gauss-markov signals in noise: closed-form error exponentand properties
The performance of Neyman-Pearson detection of correlated random signals using noisy
observations is considered. Using the large deviations principle, the performance is …
observations is considered. Using the large deviations principle, the performance is …
Moderate Deviations for Parameter Estimation in the Fractional Ornstein–Uhlenbeck Processes with Periodic Mean
H Jiang, SM Li, WG Wang - Acta Mathematica Sinica, English Series, 2023 - Springer
In this paper, we study the asymptotic properties for the drift parameter estimators in the
fractional Ornstein–Uhlenbeck process with periodic mean function and long range …
fractional Ornstein–Uhlenbeck process with periodic mean function and long range …
Sharp large deviations for the fractional Ornstein–Uhlenbeck process
Sharp Large Deviations for the Fractional Ornstein–Uhlenbeck Process Page 1 Copyright © by
SIAM. Unauthorized reproduction of this article is prohibited. THEORY PROBAB. APPL. c 2011 …
SIAM. Unauthorized reproduction of this article is prohibited. THEORY PROBAB. APPL. c 2011 …
Detection of Gauss–Markov random fields with nearest-neighbor dependency
A Anandkumar, L Tong, A Swami - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
The problem of hypothesis testing against independence for a Gauss–Markov random field
(GMRF) is analyzed. Assuming an acyclic dependency graph, an expression for the log …
(GMRF) is analyzed. Assuming an acyclic dependency graph, an expression for the log …
A large deviation perspective on ratio observables in reset processes: robustness of rate functions
We study large deviations of a ratio observable in discrete-time reset processes. The ratio
takes the form of a current divided by the number of reset steps and as such it is not …
takes the form of a current divided by the number of reset steps and as such it is not …
Large deviations for the Ornstein-Uhlenbeck process with shift
B Bercu, A Richou - Advances in Applied Probability, 2015 - cambridge.org
We investigate the large deviation properties of the maximum likelihood estimators for the
Ornstein-Uhlenbeck process with shift. We propose a new approach to establish large …
Ornstein-Uhlenbeck process with shift. We propose a new approach to establish large …