In this paper, a class of statistics based on high frequency observations of oscillating and skew Brownian motions is considered. Their convergence rate towards the local time of the underlying process is obtained in form of a Central Limit Theorem. Oscillating and skew Brownian motions are solutions to stochastic differential equations with singular coefficients: piecewise constant diffusion coefficient or drift involving the local time. The result is applied to provide estimators of the parameter of skew Brownian motion and study their asymptotic behavior. Moreover, in the case of the classical statistic given by the normalized number of crossings, the result is proved to hold for a larger class of It\^o-processes with singular coefficients.
翻译:在本文中,根据对摇晃和扭曲布朗动议的高频观测,对一组统计数据进行了考虑;它们与基本进程当地时间的趋同率以中央限制理论的形式获得; 振动和扭曲布朗动议是用单系数解决具有单数的随机差异方程的办法:小数常数扩散系数或与当地时间有关的漂移; 其结果用于提供Skew布朗运动参数的测算器,并研究其无药可治行为; 此外,对于由正常的过境点数目给出的古典统计,结果被证明为具有单系数的较大种类的Itçã过程。