统计学系系列讲座之341-342期

统计学系系列讲座之341期

时　间：2019年5月27日（星期一）16:00-17:00

地　点：史带楼502室

主持人：朱仲义教授复旦大学管理学院统计学系

主　题：Nonparametric Testing of Lack of Dependence in Functional Linear Models

主讲人：张宝学教授　首都经济贸易大学统计学院

简　介：

张宝学教授是首都经济贸易大学统计学院院长，博士生导师。中国现场统计学会环境与资源分会副理事长、全国应用统计专业学位研究生教育指导委员会委员、中国统计教育学会高等教育分会秘书长。

摘　要：

An important inferential task in functional linear models is to test the

dependence between the response and the functional predictor. The traditional testing theory was constructed based on the functional principle component anal-ysis which requires estimating the covariance operator of the functional predictor. Due to the intrinsic high-dimensionality of functional data, the sample is often not large enough to a ord accurately estimating the covariance operator and hence

causes the follow-up test underpowered. To avoid the expensive estimation of the covariance operator, we propose a nonparametric method called Functional Linear models with U-statistics TEsting (FLUTE) to test the dependence as- sumption. We show that the FLUTE test is more powerful than the current benchmark method (Kokoszka et al., 2008). We further prove the asymptotic normality of our test statistic under both the null hypothesis and a local alter-native hypothesis. The merit of our method is demonstrated by both simulation studies and real examples, particularly in the small or moderate sample case.

统计学系

2019-5-24