报告题目：Conditional-mean multiplicative operator models for count time series

报告专家：朱复康教授

报告地点：9-122会议室

报告时间：2024年3月28日（周四）上午10:00-11:00  

报告摘要：Multiplicative error models (MEMs) are commonly used for real-valued time series, but they cannot be applied to discrete-valued count time series as the involved multiplication would not preserve the integer nature of the data. Thus, the concept of a multiplicative operator for counts is proposed (as well as several specific instances thereof), which are then used to develop a kind of MEMs for count time series (CMEMs). If equipped with a linear conditional mean, the resulting CMEMs are closely related to the class of so-called integer-valued generalized autoregressive conditional heteroscedasticity (INGARCH) models and might be used as a semi-parametric extension thereof. Important stochastic properties of different types of INGARCH-CMEM as well as relevant estimation approaches are derived, namely types of quasi-maximum likelihood and weighted least squares estimation. The performance and application are demonstrated with simulations as well as with two real-world data examples.

报告人简介：朱复康，吉林大学数学学院教授、博士生导师，吉林国家应用数学中心副主任、院长助理、概率统计与数据科学系主任。2008年博士毕业，2013年破格晋升教授，2021年任唐敖庆领军教授。主要从事时间序列分析和金融统计的研究，已经在Annals of Applied Statistics、Journal of Business & Economic Statistics、Statistica Sinica、中国科学-数学等期刊上发表论文多篇，主持国家自然科学基金面上项目3项和青年基金1项，曾获得教育部自然科学奖二等奖、吉林省科学技术奖二等奖、长春市有突出贡献专家等奖励，入选美国斯坦福大学发布的全球前2%顶尖科学奖榜单。现任中国现场统计研究会、全国工业统计学教学研究会、中国数学会概率统计分会等学会的理事或常务理事，现任SCI期刊Statistical Papers的Associate Editor，是JRSSB、JBES、AoAS等80余个SCI期刊的匿名审稿人。

作者：佘纬；编辑：刘鹍；审核：郭晖；上传：郭敏。