“Supplementary Material”(Iguchi, Beskos and Graham, 2025) provides the proofs of the main
results and related technical proofs, and also contains an additional numerical experiment of …

We study parametric inference for ergodic diffusion processes with a degenerate diffusion
matrix. Existing research focuses on a particular class of hypo-elliptic Stochastic Differential …

We consider the quasi-likelihood analysis for a linear regression model driven by a Student-t
Lévy process with constant scale and arbitrary degrees of freedom. The model is observed …

Fast and asymptotically efficient methods for the estimation of the parameters in self-excited
counting Hawkes processes are considered. They are based on the Le Cam one-step …

Abstract The stochastic FitzHugh-Nagumo (FHN) model is a two-dimensional nonlinear
stochastic differential equation with additive degenerate noise, whose first component, the …

Parameter estimation in nonlinear multivariate stochastic differential equations based on
splitting schemes Page 1 The Annals of Statistics 2024, Vol. 52, No. 2, 842–867 https://doi.org/10.1214/24-AOS2371 …

We consider a degenerate system of stochastic differential equations. The first component of
the system has a parameter $\theta _1 $ in a non-degenerate diffusion coefficient and a …

We address parameter estimation in second-order stochastic differential equations (SDEs),
prevalent in physics, biology, and ecology. Second-order SDE is converted to a first-order …

In the last decade, research and corporate have shown a dramatically growing interest in the
field of machine learning, mostly due to the performances of deep neural networks. These …

This paper considers the joint estimation of the parameters of a first-order fractional
autoregressive model. A one-step procedure is considered in order to obtain an …