Non-parametric adaptive estimation of the drift for a jump diffusion process
Abstract
In this article, we consider a jump diffusion process (Xt)observed at discrete times t=0,Delta,...,nDelta. The sampling interval Delta tends to 0 and nDelta tends to infinity. We assume that (Xt) is ergodic, strictly stationary and exponentially β-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.
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