Estimation Paramétrique dans un Contexte de Petite Diffusion Linéaire

Abstract

In this memoir, we studied parametric estimation in stochastic differential equations (SDE). After introducing the fundamental concepts, we examined the construction and asymptotic roperties of the maximum likelihood estimator. This theory was applied to the Ornstein-Uhlenbeck process, where we verified the regularity conditions and performed numerical simulations to illustrate the theoretical study.