Non-parametric adaptive estimation of the drift for a jump diffusion process

被引:21
|
作者
Schmisser, Emeline [1 ]
机构
[1] Univ Lille 1, Lab Paul Painleve, F-59655 Villeneuve Dascq, France
关键词
Jump diffusions; Nonparametric estimation; Drift estimation; Model selection; BOUNDS;
D O I
10.1016/j.spa.2013.09.012
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 article, we consider a jump diffusion process (X-t)(t >= 0) observed at discrete times t = 0, Delta, ..., n Delta. The sampling interval Delta tends to 0 and n Delta tends to infinity. We assume that (X-t)(t >= 0) is ergodic, strictly stationary and exponentially beta-mixing. We use a penalised least-square approach to compute two adaptive estimators of the drift function b. We provide bounds for the risks of the two estimators. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:883 / 914
页数:32
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