Weak variable step-size schemes for stochastic differential equations based on controlling conditional moments
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Publication:6106936
DOI10.1016/j.apnum.2023.02.008arXiv2006.06729OpenAlexW4320487133MaRDI QIDQ6106936
Carlos M. Mora, J. C. Jimenez, Mónica Selva
Publication date: 3 July 2023
Published in: Applied Numerical Mathematics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2006.06729
stochastic differential equationnumerical solutionEuler schemeweak errorMonte-Carlo methodadaptive time-stepping
Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)
Cites Work
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- A weak local linearization scheme for stochastic differential equations with multiplicative noise
- Locally linearized methods for the simulation of stochastic oscillators driven by random forces
- Adaptive stepsize based on control theory for stochastic differential equations
- A variable step-size control algorithm for the weak approximation of stochastic differential equations
- Error estimation and control for ODEs
- SDELab: A package for solving stochastic differential equations in MATLAB
- Automatic selection of the initial step size for an ODE solver
- Higher-order implicit strong numerical schemes for stochastic differential equations
- Local linearization method for the numerical solution of stochastic differential equations
- An adaptive time-stepping method based on a posteriori weak error analysis for large SDE systems
- Adaptive Euler methods for stochastic systems with non-globally Lipschitz coefficients
- Adaptive Euler-Maruyama method for SDEs with nonglobally Lipschitz drift
- First-order weak balanced schemes for stochastic differential equations
- On the weak convergence rate of an exponential Euler scheme for SDEs governed by coefficients with superlinear growth
- Loss of regularity for Kolmogorov equations
- Adaptive time-stepping for the strong numerical solution of stochastic differential equations
- Stochastic simulation and Monte Carlo methods. Mathematical foundations of stochastic simulation
- Weak local linear discretizations for stochastic differential equations: convergence and numerical schemes
- A step size control algorithm for the weak approximation of stochastic differential equations
- Hypoelliptic second order differential equations
- Evaluating numerical ODE/DAE methods, algorithms and software
- On NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations
- Multilevel Monte Carlo Methods
- Guaranteed Conservative Fixed Width Confidence Intervals via Monte Carlo Sampling
- Numerical approximations of stochastic differential equations with non-globally Lipschitz continuous coefficients
- An adaptive discretization algorithm for the weak approximation of stochastic differential equations
- Non-nested Adaptive Timesteps in Multilevel Monte Carlo Computations
- Strong and weak divergence in finite time of Euler's method for stochastic differential equations with non-globally Lipschitz continuous coefficients
- Adaptive Weak Approximation of Diffusions with Jumps
- Boundary Preserving Semianalytic Numerical Algorithms for Stochastic Differential Equations
- Variable Step Size Control in the Numerical Solution of Stochastic Differential Equations
- Balanced Implicit Methods for Stiff Stochastic Systems
- Mean-Square and Asymptotic Stability of the Stochastic Theta Method
- Adaptive time-stepping strategies for nonlinear stochastic systems
- Solving ODEs with MATLAB
- A Variable Stepsize Implementation for Stochastic Differential Equations
- Adaptive weak approximation of stochastic differential equations
- Numerical Solution of Ordinary Differential Equations
- A Stable Numerical Scheme for Stochastic Differential Equations with Multiplicative Noise
- AN INTRODUCTION TO MULTILEVEL MONTE CARLO METHODS
- Approximate linear minimum variance filters for continuous-discrete state space models: convergence and practical adaptive algorithms
- Stochastic Processes and Applications
- An adaptive Euler-Maruyama scheme for SDEs: convergence and stability
- Convergence Rates for Adaptive Weak Approximation of Stochastic Differential Equations
- Almost Sure and Moment Exponential Stability in the Numerical Simulation of Stochastic Differential Equations
- Implementation and analysis of an adaptive multilevel Monte Carlo algorithm
- Numerical Methods for Ordinary Differential Equations
- Second order PDE's in finite and infinite dimension
