题目：Semiparametric Localised Bandwidth Selection in Density Estimation
嘉宾：高集体 教授 （澳大利亚莫纳什大学）
时间：2014年9月22日下午4:15

地点：管理科研楼10楼1018会议室

单位：管理学院统计与金融系

摘要：
The use of a localized bandwidth in kernel density estimation is often more attractive than the use of a global bandwidth. Nonetheless, a difficult issue is how we can consistently estimate a localized bandwidth. In this paper, we propose a semiparametric estimation method, for which we establish an asymptotic theory for the proposed semiparametric estimator. A by-product of this bandwidth estimate is a new sampling-based likelihood approach to hyperparameter estimation. Monte Carlo simulation studies show that the proposed hyperparameter estimation method works very well, and that the proposed bandwidth estimator outperforms its competitors. Applications of the new bandwidth estimator to the kernel density estimation of Eurodollar deposit rate, as well as the S&P 500 daily return under conditional heteroscedasticity, demonstrate the effectiveness and competitiveness of the proposed semiparametric localized bandwidth.