报 告 人：张正军 教授（美国威斯康辛大学麦迪逊主校）
报告题目：Random Threshold Driven Tail Dependence Measures with Application to Precipitation Data Analysis
报告时间：2015 年12月 16日（周三）上午10：00
报告地点：静远楼1506学术报告厅
摘 要： This paper first studies the theoretical properties of the tail quotient correlation coefficient (TQCC) which was proposed to measure tail dependence between two random variables. By introducing random thresholds in TQCC, an approximation theory between conditional tail probabilities is established. The new random threshold driven TQCC can be used to test the null hypothesis of tail independence under which TQCC test statistics are shown to follow a Chi-squared distribution under two general scenarios respectively. The TQCC is shown to be consistent under the alternative hypothesis of tail dependence with a general approximation of max-stable distribution. Second, we apply TQCC to investigate tail dependencies of a large scale applied problem of daily precipitation in continental US. Our results, in the perspective of tail dependence, reveal nonstationarity, spatial clusters, and tail dependence in the precipitations cross continental US.
张正军教授简介：美国威斯康辛大学麦迪逊主校统计系教授，副系主任。2002年毕业于北卡罗来纳大学教堂山分校，获统计学博士学位；1996年毕业于北京航空航天大学，获管理工程博士学位；1993年毕业于中国科学院，获计算数学硕士学位；1986年毕业于云南大学，获计算数学学士学位。 先后担任JBES、JKSS、Statistics and Its Interface副主编，NSF、NSA、FQRNT（加拿大）专家组成员，国际顶级SCI期刊审稿人；2012-2015担任泛华统计学会理 事；2004，2005荣获美国国家自然基金新星指导荣誉奖。在包括四大天王在内的统计学杂志上发表SCI论文近30篇。