A step size control algorithm for the weak approximation of stochastic differential equations
A step size control algorithm for the weak approximation of stochastic differential equations
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DOI：
10.1007/s11075-007-9108-0
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发表时间：
2007-07
影响因子：
2.1
通讯作者：
D. Küpper;J. Lehn;A. Rössler
中科院分区：
文献类型：
--
作者：
D. Küpper;J. Lehn;A. Rössler
介绍了一种用于随机微分方程弱逼近的变步长控制算法。该算法基于嵌入式龙格-库塔方法，产生两个不同阶的近似，而额外的计算量可以忽略不计。用这两个近似的差值作为不太精确的近似的局部误差的估计量。数值结果说明了所引入的步长控制方法的有效性。
A vriable step size control algorithm for the weak approximation of stochastic differential equations is introduced. The algorithm is based on embedded Runge–Kutta methods which yield two approximations of different orders with a negligible additional computational effort. The difference of these two approximations is used as an estimator for the local error of the less precise approximation. Some numerical results are presented to illustrate the effectiveness of the introduced step size control method.