Strong convergence results on tamed Euler schemes, which approximate stochastic differential equations with superlinearly growing drift coefficients that are locally one-sided Lipschitz continuous, are presented in this article. The diffusion coeffi-cients are assumed to be locally Lipschitz continuous and have at most linear growth. Furthermore, the classical rate of convergence, i.e. one–half, for such schemes is re-covered when the local Lipschitz continuity assumptions are replaced by global and, in addition, it is assumed that the drift coefficients satisfy polynomial Lipschitz con-tinuity
The Euler scheme is one of the standard schemes to obtain numerical approximations of solutions of s...
This paper develops strong convergence of the Euler-Maruyama (EM) schemes for approximating McKean-V...
AbstractIn this paper, we are concerned with the numerical approximation of stochastic differential ...
Traditional finite-time convergence theory for numerical methods applied to stochastic differential ...
We extend the taming techniques for explicit Euler approximations of stochastic differential equatio...
We consider one-dimensional stochastic differential equations in the particular case of diffusion c...
We consider the long-time behavior of an explicit tamed Euler scheme applied to a class of stochasti...
We provide a rate for the strong convergence of Euler approximations for stochastic differential equ...
Tambue A, Mukam JD. Strong convergence and stability of the semi-tamed and tamed Euler schemes for s...
In traditional works on numerical schemes for solving stochastic differential equations (SDEs), the ...
The main purpose of this paper is to investigate the strong convergence of the Euler method to stoch...
We consider the approximation of one-dimensional stochastic differential equations (SDEs) with non-L...
Abstract: Stochastic differential equations provide a useful means of intro-ducing stochasticity int...
AbstractWe provide a rate for the strong convergence of Euler approximations for stochastic differen...
Traditional finite-time convergence theory for numerical methods applied to stochastic differential ...
The Euler scheme is one of the standard schemes to obtain numerical approximations of solutions of s...
This paper develops strong convergence of the Euler-Maruyama (EM) schemes for approximating McKean-V...
AbstractIn this paper, we are concerned with the numerical approximation of stochastic differential ...
Traditional finite-time convergence theory for numerical methods applied to stochastic differential ...
We extend the taming techniques for explicit Euler approximations of stochastic differential equatio...
We consider one-dimensional stochastic differential equations in the particular case of diffusion c...
We consider the long-time behavior of an explicit tamed Euler scheme applied to a class of stochasti...
We provide a rate for the strong convergence of Euler approximations for stochastic differential equ...
Tambue A, Mukam JD. Strong convergence and stability of the semi-tamed and tamed Euler schemes for s...
In traditional works on numerical schemes for solving stochastic differential equations (SDEs), the ...
The main purpose of this paper is to investigate the strong convergence of the Euler method to stoch...
We consider the approximation of one-dimensional stochastic differential equations (SDEs) with non-L...
Abstract: Stochastic differential equations provide a useful means of intro-ducing stochasticity int...
AbstractWe provide a rate for the strong convergence of Euler approximations for stochastic differen...
Traditional finite-time convergence theory for numerical methods applied to stochastic differential ...
The Euler scheme is one of the standard schemes to obtain numerical approximations of solutions of s...
This paper develops strong convergence of the Euler-Maruyama (EM) schemes for approximating McKean-V...
AbstractIn this paper, we are concerned with the numerical approximation of stochastic differential ...