activity
20242026
collaborators

7 papers

math.ST2026

Drift estimation for rough processes under small noise asymptotic : QMLE approach

Arnaud Gloter, Nakahiro Yoshida

We consider a process $X^\ve$ solution of a stochastic Volterra equation with an unknown parameter in the drift function. The Volterra kernel is singular near zero, exhi…

math.ST2026

Drift estimation for rough processes under small noise asymptotic : trajectory fitting method

Arnaud Gloter, Nakahiro Yoshida

We consider a process $X^\ve$ that solves a stochastic Volterra equation with an unknown parameter in the drift function. The Volterra kernel is singular, and includes a…

math.ST2026

On the role of symmetry for staircase mechanisms in local differential privacy efficiency across different privacy regimes

Chiara Amorino, Arnaud Gloter

We investigate the structural foundations of statistical efficiency under -local differential privacy, with a focus on maximizing Fisher information. Building on the role of co…

math.ST2025

Nonparametric estimation of the stationary density for Hawkes-diffusion systems with known and unknown intensity

Chiara Amorino, Charlotte Dion-Blanc, Arnaud Gloter +1

We investigate the nonparametric estimation problem of the density , representing the stationary distribution of a two-dimensional system $\left(Z_t\right)_{t \in[0, T]}=\left(…

math.ST2025

Factorization by extremal privacy mechanisms: new insights into efficiency

Chiara Amorino, Arnaud Gloter

We study the problem of efficiency under local differential privacy ( LDP) in both discrete and continuous settings. Building on a factorization lemma, which shows that an…

math.ST2025

Minimax rate for multivariate data under componentwise local differential privacy constraints

Chiara Amorino, Arnaud Gloter

Our research delves into the balance between maintaining privacy and preserving statistical accuracy when dealing with multivariate data that is subject to \textit{componentwise lo…