1、举办单位：数学科学学院

2、活动主题：Structural change detection in ordinal time series

3、活动形式：学术报告听讲

4、活动摘要：Change-point detection in health care data has recently obtained considerable attention due to the increased availability of complex data in real-time. In many applications, the observed data is an ordinal time series. Two kinds of test statistics are proposed to detect the structural change of cumulative logistic regression model, which is often used in applications for the analysis of ordinal time series. One is the standardized efficient score vector, the other one is the quadratic form of the efficient score vector with a weight function. Under the null hypothesis, we derive the asymptotic distribution of the two test statistics, and prove the consistency under the alternative hypothesis. We also study the consistency of the change-point estimator, and a binary segmentation procedure is suggested for estimating the locations of possible multiple change-points. Simulation results show that the former statistic performs better when the change-point occurs at the centre of the data, but the latter is preferable when the change-point occurs at the beginning or end of the data. Furthermore, the former statistic could find the reason for rejecting the null hypothesis. Finally, we apply the two test statistics to a group of sleep data, the results show that there exists a structural change in the data.

5、主讲人简介：李拂晓，2012年和2015年在西北工业大学分别获得理学硕士和理学博士学位，2013年至2014年在加拿大阿尔伯塔大学统计系联合培养一年，现为西安理工大学理学院应用数学系讲师。主要研究方向是时间序列和面板数据模型的变点分析，先后在统计期刊《Sequential Analysis》，《Communications in Statistics-Theory and Methods》,《Journal of the Korean Statistical Society》等国内外刊物上发表相关学术论文十余篇。主持国家自然科学基金青年项目，陕西省自然科学基础研究计划项目，陕西省教育厅专项科学研究计划项目各一项。

6、听众范围：研究生

7、举办时间：2021/10/21

8、举办地点：腾讯会议，会议 ID：708 932 520