Weak error analysis for strong approximation schemes of SDEs with super-linear coefficients
Numerical Analysis
2023-03-29 v2 Numerical Analysis
Abstract
We present an error analysis of weak convergence of one-step numerical schemes for stochastic differential equations (SDEs) with super-linearly growing coefficients. Following Milstein's weak error analysis on the one-step approximation of SDEs, we prove a general conclusion on weak convergence of the one-step discretization of the SDEs mentioned above. As applications, we show the weak convergence rates for several numerical schemes of half-order strong convergence, such as tamed and balanced schemes. Numerical examples are presented to verify our theoretical analysis.
Cite
@article{arxiv.2303.14748,
title = {Weak error analysis for strong approximation schemes of SDEs with super-linear coefficients},
author = {Xiaojie Wang and Yuying Zhao and Zhongqiang Zhang},
journal= {arXiv preprint arXiv:2303.14748},
year = {2023}
}
Comments
This should be the replacement of the arxiv article 2112.15102 but not a new submission.