题目：Detecting multiple change points: the PULSE criterion

报告人：朱力行

时间：12月1日15：00-17：00

腾讯会议：425 118 740

个人简介：朱力行，北京师范大学统计与数据科学研究中心首席专家，北京师范大学统计学院教授委员会主席，香港浸会大学荣休讲座教授。美国科学促进会(AAAS)，美国统计学会(ASA)，以及美国数理统计研究院(IMS) fellow，国际统计研究院(ISI) elected member。分别于1989年，2014年获国家教委科学技术进步二等奖和中国教育部自然科学奖二等奖；2013年度国家自然科学奖二等奖（独立获奖人）。1998年获德国洪堡研究奖（中国自然科学领域第一位获奖者，亚洲统计学界唯一获奖者）；1997年获国家基金委杰出青年基金。

报告摘要：To avoid either intensive computation exhaustive search-based optimization algorithms may have or false positive problem hypothesis testing-based procedures encounter, we in this paper revisit change points detection of means and of variances in a sequence of observations and propose a novel criterion by a signal statistic to define consistent estimation even when the number of change points can go to infinity at a certain rate as the sample size goes to infinity. The signal statistic exhibits a useful "PULSE" pattern near change points such that we can simultaneously identify all change points. The estimation consistency can hold for the number of change points and for locations in a certain sense. Further, because of its visualization nature, in practice, the locations can also be relatively more easily identified by plots than existing methods in the literature. The method can also detect weak signals in the sense that those changes go to zero. As a generic methodology, it may be extendable to handle with other models. The numerical studies we conduct validate its good performance.