Strong convergence of explicit numerical schemes for stochastic differential equations with piecewise continuous arguments
Author:
Funder
The National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics
Link
https://link.springer.com/content/pdf/10.1007/s11075-023-01723-6.pdf
Reference26 articles.
1. Mao, X.R.: The truncated Euler-Maruyama method for stochastic differential equations. J. Comput. Appl. Math. 290, 370–384 (2015). https://doi.org/10.1016/j.cam.2015.06.002
2. Mao, X.R.: Convergence rates of the truncated Euler-Maruyama method for stochastic differential equations. J. Comput. Appl. Math. 296, 362–375 (2016). https://doi.org/10.1016/j.cam.2015.09.035
3. Guo, Q., Liu, W., Mao, X.R., Yue, R.X.: The partially truncated Euler-Maruyama method and its stability and boundedness. Appl. Numer. Math. 115, 235–251 (2017). https://doi.org/10.1016/j.apnum.2017.01.010
4. Lan, G.Q., Xia, F.: Strong convergence rates of modified truncated EM method for stochastic differential equations. J. Comput. Appl. Math. 334, 1–17 (2018). https://doi.org/10.1016/j.cam.2017.11.024
5. Li, X.Y., Mao, X.R., Yin, G.: Explicit numerical approximations for stochastic differential equations in finite horizons and in infinite horizons: truncation methods, convergence in pth moments and stability. IMA J. Numer. Anal. 39(2), 847–892 (2019). https://doi.org/10.1093/imanum/dry059
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1. Convergence of a partially truncated Euler-Maruyama method for SDEs with super-linear piecewise continuous drift and Hölder diffusion coefficients;Numerical Algorithms;2024-09-04
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