Modeling normalcy-dominant ordinal time series: An application to air quality level

报告人：朱复康

报告地点：腾讯会议ID:712-743-233

报告时间：2022年11月18日星期五10:00-11:00

报告摘要:

Inspired by the study of air quality level data, we propose a new model for the normalcy-dominant ordinal time series. The proposed model is based on a new zero-one-inflated bounded Poisson distribution with an autoregressive feedback mechanism in intensity. Under certain conditions, the stationarity and maximum likelihood estimation are established for the model. Moreover, a Lagrange multiplier test is constructed to detect the inflation phenomenon in the model. Applications find that the model can adequately capture the air quality level data in 30 major cities in China. More importantly, we use the fitted models to make the overall and dynamic air quality rankings for these cities, and finds that both rankings are rational and informative to the public.

主讲人简介：

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、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年被聘为“唐敖庆学者”领军教授B岗。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等期刊上发表论文50余篇，其中入选ESI前1%高被引论文2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等科研奖励。现任中国现场统计研究会、中国数学会概率统计学会、全国工业统计学教学研究会等学会的理事或常务理事，是JRSSB、JBES、AoAS等70余个SCI期刊的匿名审稿人。