Minimal Errors for Strong and Weak Approximation of Stochastic Differential Equations-Reference-Cited by-同舟云学术

Minimal Errors for Strong and Weak Approximation of Stochastic Differential Equations

Published:2008 Issue: Volume: Page:53-82
ISSN:
Container-title:Monte Carlo and Quasi-Monte Carlo Methods 2006
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Author:

Müller-Gronbach Thomas,Ritter Klaus

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-74496-2_4.pdf

Reference68 articles.

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3. B. Boufoussi and C. A. Tudor. Kramers-Smoluchowski approximation for stochastic evolution equations with FBM. Rev. Roumaine Math. Pures Appl. 50, 125-136 (2005).

4. S. Cambanis and Y. Hu. Exact convergence rate of the Euler-Maruyama scheme, with application to sampling design. Stochastics Stochastics Rep. 59, 211-240 (1996).

5. J. M. C. Clark and R. J. Cameron. The maximum rate of conver-gence of discrete approximations for stochastic differential equations.In: Stochastic Differential Systems (B. Grigelionis, ed.), Lect. Notes Control Inf. Sci. 25, Springer-Verlag, Berlin (1980).

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