Non-parametric adaptive estimation of the drift for a jump diffusion process
Statistics Theory
2013-09-27 v2 Statistics Theory
Abstract
In this article, we consider a jump diffusion process (X_t)observed at discrete times t=0,Delta,...,nDelta. The sampling interval Delta tends to 0 and nDelta tends to infinity. We assume that (X_t) is ergodic, strictly stationary and exponentially \beta-mixing. We use a penalized least-square approach to compute two adaptive estimators of the drift function b. We provide bounds for the risks of the two estimators.
Cite
@article{arxiv.1206.2620,
title = {Non-parametric adaptive estimation of the drift for a jump diffusion process},
author = {Emeline Schmisser},
journal= {arXiv preprint arXiv:1206.2620},
year = {2013}
}