The asymptotic error of chaos expansion approximations for stochastic differential equations

IF 0.7 Q3 STATISTICS & PROBABILITY Modern Stochastics-Theory and Applications Pub Date : 2019-06-04 DOI:10.15559/19-VMSTA133
T. Huschto, M. Podolskij, S. Sager
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引用次数: 2

Abstract

In this paper we present a numerical scheme for stochastic differential equations based upon the Wiener chaos expansion. The approximation of a square integrable stochastic differential equation is obtained by cutting off the infinite chaos expansion in chaos order and in number of basis elements. We derive an explicit upper bound for the $L^2$ approximation error associated with our method. The proofs are based upon an application of Malliavin calculus.
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随机微分方程混沌展开近似的渐近误差
本文提出了一种基于维纳混沌展开的随机微分方程的数值格式。通过对混沌序和基元数的无限混沌展开进行截断,得到了一个平方可积随机微分方程的近似解。我们为与我们的方法相关的$L^2$近似误差导出了一个显式的上界。这些证明是基于马氏微积分的一个应用。
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来源期刊
Modern Stochastics-Theory and Applications
Modern Stochastics-Theory and Applications STATISTICS & PROBABILITY-
CiteScore
1.30
自引率
50.00%
发文量
0
审稿时长
10 weeks
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