报告题目：Joint test for mean and variance change-points in long-memory time series

报告时间：2024年8月4日上午9：00

报告地点：南湖校区老图书馆四楼左侧研究生5-1学习室

主办单位：数学与统计学院

报告人：陈占寿

报告人简介：陈占寿，青海师范大学研究生院副院长，教授，博导，青海省统计学会副会长，入选青海省昆仑英才教学名师，青海省高校拔尖学科带头人等多个省级人才称号，曾访问加拿大英属各类比亚大学和中科院系统所；主要从事时间序列变点分析，小域估计、模型平均等方面的研究工作，先后主持国家自然科学基金3项，青海省自然科学基金6项；发表科研论文60余篇，出版学术专著1部，获青海省自然科学奖三等奖1项。

摘要：Abstract: In this talk, We propose two self-normalized statistics to jointly test the mean and variance change-points in long-memory time series. Under the null hypothesis that the series is a stationary long-memory process, we demonstrate that our test statistics converge to nondegenerate distributions. We derive the limit distributions of the two test statistics under three alternative hypotheses that the series has mean and variance change-points at different locations. The proposed test statistics perform well with finite samples in simulations. Moreover, we can distinguish whether a detected change-point is a mean or variance change-point, or if the mean and variance have changed together. We illustrate our tests through the analysis of two real datasets: the annual discharge volume of the Nile River, and the closing-price data of International Business Machines (IBM) common stock.