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Continuous weak approximation for stochastic differential equations

机译:随机微分方程的连续弱逼近

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摘要

A convergence theorem for the continuous weak approximation of the solution of stochastic differential equations (SDEs) by general one-step methods is proved, which is an extension of a theorem due to Milstein. As an application, uniform second order conditions for a class of continuous stochastic Runge-Kutta methods containing the continuous extension of the second order stochastic Runge-Kutta scheme due to Platen are derived. Further, some coefficients for optimal continuous schemes applicable to U SDEs with respect to a multi-dimensional Wiener process are presented. (C) 2007 Elsevier B.V. All rights reserved.
机译:证明了用一般的一步法对随机微分方程(SDE)的解进行连续弱逼近的收敛定理,这是米尔斯坦定理的一个扩展。作为一种应用,推导了一类连续随机Runge-Kutta方法的统一二阶条件,该方法包含由于Platen导致的二阶随机Runge-Kutta方案的连续扩展。此外,针对多维维纳过程,提出了适用于U SDE的最佳连续方案的一些系数。 (C)2007 Elsevier B.V.保留所有权利。

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