论文标题
在小噪声渐近学下跳投的阈值估计
Threshold estimation for jump-diffusions under small noise asymptotics
论文作者
论文摘要
我们将由维纳过程和复合泊松过程驱动的随机微分方程的参数估计作为小声音。目的是给出阈值类型的准类估计器，并在新的渐近学下显示其一致性和渐近态性。本文的新颖性是，我们给出了一个新的本地化参数，这使我们能够避免在早期作品中使用的对比函数中的截断，并处理比以往任何时候都在阈值估计中进行更广泛的跳跃。
We consider parameter estimation of stochastic differential equations driven by a Wiener process and a compound Poisson process as small noises. The goal is to give a threshold-type quasi-likelihood estimator and show its consistency and asymptotic normality under new asymptotics. One of the novelties of the paper is that we give a new localization argument, which enables us to avoid truncation in the contrast function that has been used in earlier works and to deal with a wider class of jumps in threshold estimation than ever before.
