HELLINGER AND TOTAL VARIATION DISTANCE IN APPROXIMATING LeVY DRIVEN SDES

被引：0

作者：

Clement, Emmanuelle ^{[1
]}

机构：

[1] Univ Paris Est Creteil, Univ Gustave Eiffel, CNRS, LAMA UMR 8050, Creteil, France

来源：

ANNALS OF APPLIED PROBABILITY | 2023年 / 33卷 / 03期

关键词：

Levy process; stable process; stochastic differential equation; total variation; Hellinger distance; STOCHASTIC DIFFERENTIAL-EQUATIONS; EULER APPROXIMATION; CONVERGENCE; DIFFUSION; EXISTENCE; SCHEME;

D O I：

10.1214/22-AAP1863

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper, we get some convergence rates in total variation distance in approximating discretized paths of Levy driven stochastic differential equa-tions, assuming that the driving process is locally stable. The particular case of the Euler approximation is studied. Our results are based on sharp local estimates in Hellinger distance obtained using Malliavin calculus for jump processes.

引用

页码：2176 / 2209

页数：34

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