论文标题
最小二乘估计器用于离散观察到的随机过程，由小部分噪声驱动
Least squares estimators for discretely observed stochastic processes driven by small fractional noise
论文作者
论文摘要
我们研究了由小部分噪声驱动的随机观察到的随机微分方程的参数估计问题。在某些条件下，当小分散系数收敛到0时，我们获得了最小平方估计器（LSE）的较强一致性和收敛速率，样品量会收敛到弱点。
We study the problem of parameter estimation for discretely observed stochastic differential equations driven by small fractional noise. Under some conditions, we obtain strong consistency and rate of convergence of the least square estimator(LSE) when small dispersion coefficient converges to 0 and sample size converges to infty.
