5 papers
Error of randomized Milstein scheme for scalar SDEs with noisy information about coefficients and Wiener process
PaweÅ M. Morkisz, PaweÅ PrzybyÅowicz, Martyna WiÄ cek
We investigate the strong approximation of scalar stochastic differential equations when the available standard information about the drift coefficient, the diffusion coefficient,…
Neural Network-Based Estimation of Time-Dependent Parameters in AR(p) Processes
Agnieszka KopeÄ, PaweÅ PrzybyÅowicz, Martyna WiÄ cek
We investigate a forecasting framework based on a simple discrete-time dynamic model with coefficients varying in time. The parameters of the model are recovered within a deep lear…
On the error of the Euler scheme for approximation of solutions of nonlinear DDEs under inexact information
PaweÅ PrzybyÅowicz, Martyna WiÄ cek
We analyze the behavior of the Euler method for delay differential equations under nonstandard assumptions on the right-hand-side function f, when evaluations of f are corrupted by…
On the randomized Euler scheme for SDEs with integral-form drift
PaweÅ PrzybyÅowicz, MichaÅ Sobieraj
In this paper, we investigate the problem of strong approximation of the solutions of stochastic differential equations (SDEs) when the drift coefficient is given in integral form.…
A Skorohod measurable universal functional representation of solutions to semimartingale SDEs
PaweÅ PrzybyÅowicz, Verena Schwarz, Alexander Steinicke +1
In this paper we show the existence of a universal Skorohod measurable functional representation for a large class of semimartingale-driven stochastic differential equations. For t…