“数字+”与之江统计讲坛（第139讲）10月14日香港城市大学袁淦讲座预告

讲座题目：Generalized multivariate threshold autoregressive models with linearly partitioned threshold space

主讲人：袁淦

讲座时间：2026年10月14日（周三） 15:00

讲座地点： 综合楼644会议室

主讲人简介：

　　袁淦，现就职于香港城市大学生物统计学系。香港中文大学计量金融与风险管理学士及硕士，美国哥伦比亚大学统计学博士。目前担任《数据科学期刊》(Journal of Data Science) 副主编。在学术研究领域，研究兴趣广泛，主要聚焦于非参数统计、时间序列分析、经验过程理论、函数型数据分析。研究成果陆续发表于《统计学年刊》(The Annals of Statistics)、《机器学习研究期刊》(JMLR)、《美国国家科学院院刊》(PNAS) 以及《SIAM 数据科学数学期刊》(SIMODS)等国际学术期刊上发表。

讲座摘要：

　　We consider a k-dimensional multiple-regime vector threshold autoregressive model, in which the regime-switching mechanism is governed by a bivariate threshold variable. Specifically, the regimes are induced by a partition of the threshold space by an unknown number of threshold lines. Within each regime, the process follows a specific vector autoregressive (VAR) model. We formulate the model selection and parameter estimation into a minimization problem based on the Minimum Description Length (MDL) principle and estimate the number of threshold lines, parametric forms of threshold lines and VAR model parameters in each regime simultaneously. Theoretically, we show that the MDL estimators of threshold lines are n-consistent and characterize their limiting distribution. This requires novel proving techniques of introducing a new functional space G for the local MDL difference functions and establishing weak convergence results therein. Finally, we conduct some empirical studies with simulated datasets and perform real data analyses on U.S. interest rates and U.S. GNP Data.