报告主题：Self-exciting hysteretic binomial autoregressive processes

报 告 人：杨凯 副教授

报告时间：2024年9月28日（周六）上午10：00-11：00

报告地点：腾讯会议（会议号：485334578）

报告摘要: This paper introduces an observation-driven integer-valued time seriesmodel, inwhich the underlying generating stochastic process is binomially distributed conditional on past information in the form of a hysteretic autoregressive structure. The basic probabilistic and statistical properties of the model are discussed. Conditional least squares, weighted conditional least squares, and maximum likelihood estimators are obtained together with their asymptotic properties. A search algorithm for the two boundary parameters, and the corresponding strong consistency of the estimators, are also provided. Finally, some numerical results on the estimators and a real-data example are presented.

报告人简介：杨凯，副教授，博士生导师，现任长春工业大学数学与统计学院副院长，吉林省高层次人才，曾赴日本岛根大学学术访问。主要研究领域为时间序列分析、高维数据分析、贝叶斯分析等。主持国家自然科学基金面上项目和青年基金项目各1项，吉林省自然科学基金面上项目、横向项目等共6项。以第一作者、通讯作者身份在Applied Mathematical Modelling, Computational Statistics & Data Analysis等杂志发表SCI/SSCI论文近30篇，其中二区以上论文6篇，ESI高被引论文2篇。主持省级研究生精品课建设项目1项，第四届全国高校数学微课程教学设计竞赛全国一等奖，全国应用统计专业学位研究生教育教学成果二等奖。