64 citations · 195 across the 18 of their papers we have counts for
8 papers · 1 filter
Strang Splitting for Parametric Inference in Second-order Stochastic Differential Equations
Predrag Pilipovic, Adeline Samson, Susanne Ditlevsen
We address parameter estimation in second-order stochastic differential equations (SDEs), which are prevalent in physics, biology, and ecology. The second-order SDE is converted to…
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…
Parameter Estimation in Nonlinear Multivariate Stochastic Differential Equations Based on Splitting Schemes
Predrag Pilipovic, Adeline Samson, Susanne Ditlevsen
The likelihood functions for discretely observed nonlinear continuous-time models based on stochastic differential equations are not available except for a few cases. Various param…
High-dimensional cointegration and Kuramoto systems
Jacob Stærk-Østergaard, Anders Rahbek, Susanne Ditlevsen
This paper presents a novel estimator for a non-standard restriction to both symmetry and low rank in the context of high dimensional cointegrated processes. Furthermore, we discus…
Hypoelliptic diffusions: discretization, filtering and inference from complete and partial observations
Susanne Ditlevsen, Adeline Samson
The statistical problem of parameter estimation in partially observed hypoelliptic diffusion processes is naturally occurring in many applications. However, due to the noise struct…
Multivariate inhomogeneous diffusion models with covariates and mixed effects
Mareile Große Ruse, Adeline Samson, Susanne Ditlevsen
Modeling of longitudinal data often requires diffusion models that incorporate overall time-dependent, nonlinear dynamics of multiple components and provide sufficient flexibility…
Parameter inference from hitting times for perturbed Brownian motion
M. Tamborrino, S. Ditlevsen, P Lansky
A latent internal process describes the state of some system, e.g. the social tension in a political conflict, the strength of an industrial component or the health status of a per…
Estimation in the partially observed stochastic Morris-Lecar neuronal model with particle filter and stochastic approximation methods
Susanne Ditlevsen, Adeline Samson
Parameter estimation in multidimensional diffusion models with only one coordinate observed is highly relevant in many biological applications, but a statistically difficult proble…