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首页> 外文期刊>SIAM Journal on Numerical Analysis >Error analysis for approximation of stochastic differential equations driven by Poisson random measures
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Error analysis for approximation of stochastic differential equations driven by Poisson random measures

机译:泊松随机测度驱动随机微分方程近似的误差分析

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摘要

Let X-t be the solution of a stochastic differential equation ( SDE) with starting point x(0) driven by a Poisson random measure. Additive functionals are of interest in various applications. Nevertheless they are often unknown and can only be found by simulation on computers. We investigate the quality of the Euler approximation. Our main emphasis is on SDEs driven by an alpha-stable process, 0 < α< 2, where we study the approximation of the Monte Carlo error E [f (X-T)], f belonging to L-infinity. Moreover, we treat the case where the time equals Tboolean AND tau, where tau is the first exit time of some interval. [References: 17]
机译:设X-t为随机微分方程(SDE)的解,其起始点x(0)由泊松随机测度驱动。附加功能在各种应用中都令人感兴趣。但是,它们通常是未知的,只能通过在计算机上进行仿真才能找到。我们研究欧拉近似的质量。我们主要强调由α稳定过程(0 <α<2)驱动的SDE,在这里我们研究属于L-无穷大的蒙特卡罗误差E [f(X-T)] f的近似值。此外,我们处理时间等于Tboolean AND tau的情况,其中tau是某个时间间隔的第一个退出时间。 [参考:17]

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