Chenggui Yuan

Chenggui Yuan


Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2011 in Stochastic Processes and their Applications
Verified
Journal Article
Closed access
Feng-Yu WangFeng-Yu Wang
Feng-Yu Wang
CYChenggui Yuan
Chenggui Yuan

16 December 2015 in Potential Analysis
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Journal Article
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JBJianhai Bao
Jianhai Bao
JSJinghai Shao
Jinghai Shao
CYChenggui Yuan
Chenggui Yuan

23 July 2011 in Acta Applicandae Mathematicae
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Journal Article
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JBJianhai Bao
Jianhai Bao
CYChenggui Yuan
Chenggui Yuan

31 August 2018 in Journal of Theoretical Probability
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Journal Article
Open access
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JBJianhai Bao
Jianhai Bao
XHXing Huang
Xing Huang
CYChenggui Yuan
Chenggui Yuan
In this paper, we are concerned with convergence rate of Euler–Maruyama scheme for stochastic differential equations with Hölder–Dini continuous drifts. The key contributions are as follows: (i) by means of regularity of non-degenerate Kolmogrov equation, we investigate convergence rate of Euler–Maruyama scheme for a class of stochastic differential equations which allow the drifts to be Dini continuous and unbounded; (ii) by the aid of regularization properties of degenerate Kolmogrov equation, we discuss convergence rate of Euler–Maruyama scheme for a range of degenerate stochastic differential equations where the drifts are Hölder–Dini continuous of order \(\frac{2}{3}\) with respect to the first component and are merely Dini-continuous concerning the second component.

22 June 2009 in Stochastic Analysis and Applications
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Journal Article
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NJNiels Jacob
Niels Jacob
YWYongtian Wang
Yongtian Wang
CYChenggui Yuan
Chenggui Yuan
In this article, we investigate the strong convergence of the Euler–Maruyama method and stochastic theta method for stochastic differential delay equations with jumps. Under a global Lipschitz condition, we not only prove the strong convergence, but also obtain the rate of convergence. We show strong convergence under a local Lipschitz condition and a linear growth condition. Moreover, it is the first time that we obtain the rate of the strong convergence under a local Lipschitz condition and a linear growth condition, i.e., if the local Lipschitz constants for balls of radius R are supposed to grow not faster than log R.

7 March 2008 in Stochastic Analysis and Applications
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Journal Article
Closed access
CYChenggui Yuan
Chenggui Yuan
Xuerong MaoXuerong Mao
Xuerong Mao
The recent article [ 2 Higham , D.J. , Mao , X. , and Stuart , A.M. 2002 . Strong convergence of numerical methods for nonlinear stochastic differential equations . SIAM J. Num. Anal. 40 : 1041 – 1063 . [Crossref], [Web of Science ®] [Google Scholar] ] reveals the strong convergence of the Euler–Maruyama solution to the exact solution of a stochastic differential equation under the local Lipschitz condition. However, it does not provide us with an order of convergence. In this note, we will show the rate of convergence still under the local Lipschitz condition, but the local Lipschitz constants of the drift coefficient, valid on balls of radius R, are supposed not to grow faster than log R while those of the diffusion coefficient are not than .