Date: 2023-09-28

Time: 14:00-15:00 (UK time)

Strand S5.20

Abstract

Multivariate nonlinear Hawkes processes are powerful models for multi- variate point processes with excitation and inhibition phenomenon. Bayesian nonparametric methods have been proposed and studied theoretically, showing good properties. However their implementation remain a challenge due to the complexity of the likelihood and the potentially high dimensional space. In this work we propose a two step variational Bayes approach to estimate both the graph of interaction and the functions of interactions. We give theoretical guarantees to the procedure and show that it scales well for moderately high dimensional Hawkes processes. This is a joint work with Deborah Sulem and Vincent Rivoirard.

Speaker

Judith Rousseau is a professor of statistics at the University of Oxford and at the University Paris Dauphine. Her research interests range from theoretical aspects of Bayesian procedures, both parametric and nonparametric, to more methodological developments. She is interested in the interface between Bayesian and frequentist approaches, looking at frequentist properties of Bayesian methods in complex, high dimensional or nonparametric models. She has also worked on MCMC or related algorithms or on the elicitation of subjective priors.