34 citations · 51 across the 13 of their papers we have counts for
14 papers
Bayesian Analysis of Covariate-Driven Hawkes Processes with Application in Plant Epidemiology
Katarzyna Adamczyk-Chauvat, Madalina Deaconu, Sylwester Masny +1
Hawkes processes are widely used to model temporal point patterns exhibiting self-exciting behavior. In this work, we consider a Hawkes model with a baseline intensity depending on…
Hug model: parameter estimation via the ABC Shadow algorithm
Christophe Reype, Radu S. Stoica, Didier Gemmerlé +2
Studying geological fluids mixing systems allows to understand interaction among water sources. The Hug model is an interaction point process model that can be used to estimate the…
HUG model: an interaction point process for Bayesian detection of multiple sources in groundwaters from hydrochemical data
Christophe Reype, Radu S. Stoica, Antonin Richard +1
This paper presents a new interaction point process that integrates geological knowledge for the purpose of automatic sources detection of multiple sources in groundwaters from hyd…
Strong approximation of Bessel processes
Madalina Deaconu, Samuel Herrmann
We consider the path approximation of Bessel processes and develop a new and efficient algorithm. This study is based on a recent work by the authors, on the path approximation of…
Bayesian statistical analysis of hydrogeochemical data using point processes: a new tool for source detection in multicomponent fluid mixtures
Christophe Reype, Antonin Richard, Madalina Deaconu +1
Hydrogeochemical data may be seen as a point cloud in a multi-dimensional space. Each dimension of this space represents a hydrogeochemical parameter (i.e. salinity, solute concent…
Strong approximation of particular one-dimensional diffusions
Madalina Deaconu, Samuel Herrmann
This paper develops a new technique for the path approximation of one-dimensional stochastic processes, more precisely the Brownian motion and families of stochastic differential e…