Convergence rate of weak Local Linearization schemes for stochastic differential equations with additive noise

被引:9
|
作者
Jimenez, J. C. [1 ]
Carbonell, F. [2 ]
机构
[1] Inst Cibemet Matemat & Fis, Havana 10400, Cuba
[2] Biospective Inc, Montreal, PQ, Canada
关键词
Local Linearization schemes; Stochastic differential equations; Additive noise; Numerical integration; SQUARE NUMERICAL-METHODS; LINEAR DISCRETIZATIONS; MAXIMUM-LIKELIHOOD; MATRIX; MODELS; SYSTEMS; COMPUTE;
D O I
10.1016/j.cam.2014.10.021
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
There exists a diversity of weak Local Linearization (LL) schemes for the integration of stochastic differential equations with additive noise, which differ in the algorithms employed for the numerical implementation of the weak Local Linear discretizations. Despite convergence results for these discretizations have been already developed, the convergence of the weak LL schemes has not been considered up to date. In this work, a general result concerning the convergence rate of the weak LL schemes is presented, as well as specificities for a number of particular schemes. As an application, the convergence of weak LL schemes for equations driven by Poisson processes is presented in addition. (C) 2014 Elsevier B.V. All rights reserved.
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页码:106 / 122
页数:17
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