Minimal asymptotic error for one-point approximation of SDEs with time-irregular coefficients
DOI10.1016/j.cam.2015.01.003zbMath1322.65015OpenAlexW2005515012MaRDI QIDQ2255720
Publication date: 18 February 2015
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cam.2015.01.003
convergencestochastic differential equationsMonte Carlo methodsasymptotic errorlower boundsoptimal algorithmnon-standard assumptionsone-point approximationrandomized Euler scheme
Monte Carlo methods (65C05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Stability and convergence of numerical methods for ordinary differential equations (65L20) Ordinary differential equations and systems with randomness (34F05) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)
Related Items (max. 100)
Cites Work
- Unnamed Item
- Unnamed Item
- Complexity of the derivative-free solution of systems of IVPs with unknown singularity hypersurface
- Optimal adaptive solution of piecewise regular systems of IVPs with unknown switching hypersurface
- Adaptive Itô-Taylor algorithm can optimally approximate the Itô integrals of singular functions
- Asymptotic error of algorithms for solving nonlinear problems
- Higher-order implicit strong numerical schemes for stochastic differential equations
- Deterministic and stochastic error bounds in numerical analysis
- Error analysis of a randomized numerical method
- Optimal pointwise approximation of SDEs based on Brownian motion at discrete points
- The Euler scheme with irregular coefficients
- The optimal uniform approximation of systems of stochastic differential equations
- Asymptotic setting (revisited): analysis of a boundary-value problem and a relation to a classical approximation result
- Weak rate of convergence of the Euler-Maruyama scheme for stochastic differential equations with non-regular drift
- Numerical methods for systems with measurable coefficients
- Strong approximation of solutions of stochastic differential equations with time-irregular coefficients via randomized Euler algorithm
- The randomized complexity of initial value problems
- A random Euler scheme for Carathéodory differential equations
- Adaption allows efficient integration of functions with unknown singularities
- Improved bounds on the randomized and quantum complexity of initial-value problems
- Theoretical Numerical Analysis
- Strong rate of convergence for the Euler-Maruyama approximation of stochastic differential equations with irregular coefficients
- Optimality of Euler-type algorithms for approximation of stochastic differential equations with discontinuous coefficients
- The power of adaption for approximating functions with singularities
This page was built for publication: Minimal asymptotic error for one-point approximation of SDEs with time-irregular coefficients