Southwest Jiaotong University School of Mathematics

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新加坡国立大学统计系张金廷教授学术报告

来源:   作者:黄磊     日期:2018-09-05 08:49:54   点击数:  

报告人: 张金廷教授,出生在中国广东省龙川县。早年在北京大学取得学士学位,在中国科学院应用数学所取得硕士学位, 在美国北卡莱那大学教堂山分校取得博士学位,曾在哈佛大学做博士后。先后在美国普林斯顿,罗泽斯特等大学做高级访问学者。现任新加坡国立大学概率统计系终身教授,博士生、博士后导师。他先后培养了数十个硕士和七个博士以及三个博士后。他发表了数十篇学术论文,两本统计专著,和一本学术论文集。他现任和曾任几家学术期刊的编委。他曾是几次大型国际会议的组织委员。张金廷教授现在的研究领域包括非参数统计,纵向数据分析,函数数据分析,高维数据分析,等等。

报告地点:X2511

报告时间:2018925日周二,上午10:30

报告题目:New Tests for Equality of Several Covariance Functions for Functional Data

摘要:In this talk, we discuss two new tests for the equality of the covariance functions of several functional populations, namely a quasi GPF test and a quasi Fmax test whose test statistics are obtained via Globalizing a Point-wise quasi F-test statistic with integration and taking its supremum over some time interval of interest, respectively. Unlike several existing tests, they are scale-invariant in the sense that their test statistics will not change if we multiply each of the observed functions by any non-zero function of time. We derive the asymptotic random expressions of the two tests under the null hypothesis and show that under some mild conditions, the asymptotic null distribution of the quasi GPF test is a chi-squared-type mixture whose distribution can be well approximated by a simple scaled chi-squared distribution. We also propose a random permutation method for approximating the null distributions of the quasi GPF and Fmax tests. Simulation studies are presented to demonstrate the finite-sample performance of the new tests against five existing tests. An illustrative example is also presented.