Undiased monte carlo estimators for functionals of weak solutions of stochastic diffretial equations
Undiased monte carlo estimators for functionals of weak solutions of stochastic diffretial equations
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随机微分方程弱解泛函的无离散蒙特卡罗估计
DOI：
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发表时间：
1989
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通讯作者：
W. Wagner
中科院分区：
文献类型：
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作者：
W. Wagner
考虑了随机微分方程弱解泛函的一种新的数值计算格式。该方案避免了随机微分方程时间离散所带来的系统误差。它适用于广泛的一类泛函没有通常的光滑性假设。该方法是基于无偏估计的过渡密度oft的解决方案的过程，而不是个人的轨迹近似。标准的蒙特卡罗技术（冯诺依曼-乌拉姆计划）的开发和应用到柯尔莫哥洛夫向后方程。新格式包括了著名的欧拉格式和一些随机修正项
A new numerical scheme for the evaluation of functional of weak solutions of Stochastic differential equations is considered. The scheme avoids the systematic error resulting from the discretisation in time of the stochastic differential equation. It is applicable to a wide class of functionals without the usual smoothness assumptions. The approach is based on the unbiased estimation of the transition density oft the solution process instead of the approximation of individual trajectories. Standard Monte Carlo techniques (the von Neumann-Ulam scheme) are developed and applied to the Kolmogorov backward equation. The new scheme includes the well known Euler scheme associated with some random correction term