7 citations · 11 across the 5 of their papers we have counts for
6 papers
Splitting methods for stochastic Hodgkin-Huxley type systems and a localized fundamental mean-square convergence theorem
Pierre Étoré, Anna Melnykova, Irene Tubikanec
Existing fundamental theorems for mean-square convergence of numerical methods for stochastic differential equations (SDEs) require globally or one-sided Lipschitz continuous coeff…
Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length
Katerina Hlavackova-Schindler, Anna Melnykova, Irene Tubikanec
Multivariate Hawkes processes (MHPs) are versatile probabilistic tools used to model various real-life phenomena: earthquakes, operations on stock markets, neuronal activity, virus…
Non-asymptotic statistical test of the diffusion coefficient of stochastic differential equations
Anna Melnykova, Patricia Reynaud-Bouret, Adeline Samson
We develop several statistical tests of the determinant of the diffusion coefficient of a stochastic differential equation, based on discrete observations on a time interval $[0,T]…
Theoretical analysis and simulation methods for Hawkes processes and their diffusion approximation
Julien Chevallier, Anna Melnykova, Irene Tubikanec
Oscillatory systems of interacting Hawkes processes with Erlang memory kernels were introduced in Ditlevsen (2017). They are piecewise deterministic Markov processes (PDMP) and can…
Horizontal gene transfer: numerical comparison between stochastic and deterministic approaches
Vincent Calvez, Susely Figueroa Iglesias, Hélène Hivert +3
Horizontal gene Transfer (HT) denotes the transmission of genetic material between two living organisms, while the vertical transmission refers to a DNA transfer from parents to th…
Parametric inference for hypoelliptic ergodic diffusions with full observations
Anna Melnykova
Multidimensional hypoelliptic diffusions arise naturally in different fields, for example to model neuronal activity. Estimation in those models is complex because of the degenerat…