报告题目：A zero-modified geometric INAR(1) model for analyzing count time series with multiple features
报 告 人：康尧 助理教授 西安交通大学
报告时间：2022年12月3日 13:30-14:30
报告地点：腾讯会议ID：117-634-740
或点击链接直接加入会议：https://meeting.tencent.com/dm/ZQNQU2R6GEEZ
校内联系人：程建华 chengjh@jlu.edu.cn
报告摘要：Zero inflation, zero deflation, overdispersion and underdispersion are commonly encountered in count time series. To better describe these characteristics of counts, this paper introduces a zero-modified geometric INAR(1) model based on the generalized negative binomial thinning operator, which contains dependent zero-inflated geometric counting series. The new model contains the NGINAR(1) model, ZMGINAR(1) model and GNBINAR(1) model with geometric marginals as special cases. Some statistical properties are studied and estimates of the model parameters are derived by the Yule-Walker, conditional least squares and maximum likelihood methods. Asymptotic properties and numerical results of the estimates are also studied. Besides, some test and forecasting problems are addressed. Three real data examples are given to show the flexibility and practicability of the new model.
报告人简介：康尧，助理教授，现就职于西安交通大学数学与统计学院统计系。主要研究领域包括时间序列分析、保险精算。主持国家自然科学青年基金项目1项，国家博士后科学基金面上项目1项，以第一作者在Test、The Canadian Journal of Statistics等杂志发表(接收)SCI论文7篇。
