179 citations · 335 across the 13 of their papers we have counts for
19 papers
Maximum likelihood estimator for skew Brownian motion: the convergence rate
Antoine Lejay, Sara Mazzonetto
We give a thorough description of the asymptotic property of the maximum likelihood estimator (MLE) of the skewness parameter of a Skew Brownian Motion (SBM). Thanks to recent resu…
Beyond the delta method
Antoine Lejay, Sara Mazzonetto
We give an asymptotic development of the maximum likelihood estimator (MLE), or any other estimator defined implicitly, in a way which involves the limiting behavior of the score a…
General diffusion processes as the limit of time-space Markov chains
Alexis Anagnostakis, Antoine Lejay, Denis Villemonais
We prove the convergence of the law of grid-valued random walks, which can be seen as time-space Markov chains, to the law of a general diffusion process. This includes processes w…
Constructing general rough differential equations through flow approximations
Antoine Lejay
The non-linear sewing lemma constructs flows of rough differential equations from a braod class of approximations called almost flows. We consider a class of almost flows that coul…
The non-linear sewing lemma III: Stability and generic properties
Antoine Brault, Antoine Lejay
Solutions of Rough Differential Equations (RDE) may be defined as paths whose increments are close to an approximation of the associated flow. They are constructed through a discre…
The non-linear sewing lemma II: Lipschitz continuous formulation
Antoine Brault, Antoine Lejay
We give an unified framework to solve rough differential equations. Based on flows, our approach unifies the former ones developed by Davie, Friz-Victoir and Bailleul. The main ide…