Français
EnglishColloquium Catherine Matias (titre à venir)
Jeudi, 17 mars 2022 - 11:30 - 12:30
Exposé
Colloquium Nicolas Curien (titre à venir)
Jeudi, 31 mars 2022 - 11:30 - 12:30
Colloquium Matthieu Lerasle (titre à venir)
Jeudi, 3 février 2022 - 11:30 - 12:30
Efficient estimation for nonparametric regression with small intensity noise
Jeudi, 28 octobre 2021 - 10:15 - 11:15
We develop an efficient nonparametric estimation theory for continuous time regression models with non-Gaussian Lévy noises in the case when the unknown functions belong to Sobolev ellipses. Using the Pinsker’s approach, we provide a sharp lower bound for the normalized asymptotic mean square accuracy. We find constructive sufficient conditions for the ellipse coefficients under which we develop efficient estimation methods. We show that the obtained conditions hold for the ellipse coefficients of an exponential form.
(à venir)
Jeudi, 18 novembre 2021 - 10:15 - 11:15
à venir
Colloquium Pierre Cardaliaguet (titre à venir)
Jeudi, 27 janvier 2022 - 11:30 - 12:30
Colloquium Marc Lavielle (titre à venir)
Jeudi, 18 novembre 2021 - 11:30 - 12:30
Iterative Methods for Linear Systems
Mardi, 19 octobre 2021 - 11:30 - 12:30
Iterative methods for linear systems were invented for the same reasons as they are used today, namely to reduce computational cost. Gauss states in a letter to his friend Gerling in 1823: "you will in the future hardly eliminate directly, at least not when you have more than two unknowns".
(à venir)
Jeudi, 2 décembre 2021 - 10:15 - 11:15
à venir
Spectral estimation of Hawkes processes from count data
Spectral estimation of Hawkes processes from count data
Jeudi, 14 octobre 2021 - 10:15 - 11:15
Hawkes processes are a family of stochastic processes for which the occurrence of any event increases the probability of further events occurring. When count data are only observed in discrete time, we propose a spectral approach for the estimation of Hawkes processes, by means of Whittle's estimation method. To get asymptotic properties for the estimator, we prove alpha-mixing properties for the series of counts, using the Galton-Watson properties of the cluster representation of Hawkes processes.
