5 citations · 10 across the 9 of their papers we have counts for
10 papers
Stochastic compliance/evasion dynamics in tax models: a piecewise deterministic Markov process approach
Jonas Mayr, Amira Meddah, Irene Tubikanec
This paper introduces a novel stochastic framework for modelling tax evasion dynamics by extending the deterministic model of Bertotti and Modanese (2018) through the use of Piecew…
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…
Approximate Bayesian computation for stochastic hybrid systems with ergodic behaviour
Sascha Desmettre, Agnes Mallinger, Amira Meddah +1
Piecewise diffusion Markov processes (PDifMPs) form a versatile class of stochastic hybrid systems that combine continuous diffusion processes with discrete event-driven dynamics,…
Inference for the stochastic FitzHugh-Nagumo model from real action potential data via approximate Bayesian computation
Adeline Samson, Massimiliano Tamborrino, Irene Tubikanec
The stochastic FitzHugh-Nagumo (FHN) model is a two-dimensional nonlinear stochastic differential equation with additive degenerate noise, whose first component, the only one obser…
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…
Network inference via approximate Bayesian computation. Illustration on a stochastic multi-population neural mass model
Susanne Ditlevsen, Massimiliano Tamborrino, Irene Tubikanec
In this article, we propose an adapted sequential Monte Carlo approximate Bayesian computation (SMC-ABC) algorithm for network inference in coupled stochastic differential equation…