报告人：田国梁
报告地点：数学与统计学院415报告厅
报告时间：2019年11月21日星期四16:00-17:00
报告摘要：
In this paper, we propose a new multivariate Laplace distribution from normal variance mixture models, called as Type II multivariate Laplace distribution. Unlike the multivariate Laplace distribution proposed by Eltoft (2006) that all components must have the same value for the mixing variate, the random components in the new distribution could have different value for its own mixing variate and are correlated only through the dependence structure of the normal random vector. Thus, it contains the multiplication of iid univariate Laplace distributions as a special case if the normal covariance matrix is diagonal. A tractable stochastic representation (SR) is used to derive the probability density function and other statistical properties. The maximum likelihood estimates of parameters via an ECM algorithm and the Bayesian methods are derived. Some simulation studies are conducted to evaluate the performance of the proposed methods. Applications in two real data sets indicate that the Type II multivariate Laplace distribution could have a better performance and is distinct from the original one.
主讲人简介：
田国梁，南方科技大学统计与数据科学系教授、博士生导师。1988年获得武汉大学统计学硕士学位、1998年获得中国科学院应用数学研究所的统计学博士学位。从1998至2002年, 他分别在北京大学概率统计系和美国田纳西州孟斐斯市的 St. Jude 儿童研究医院生物统计系从事博士后研究, 2002年至2008年他在美国马里兰大学医学院和Marlene and Stewart Greenbaum Comprehensive 癌症中心任 Senior Biostatistician。2008年至2016年他在香港大学统计及精算学系任副教授、博士生导师。田教授是国际统计学会 (ISI) 当选会员, 他担任Computational Statistics & Data Analysis, Statistics and Its Interface 等四个国际统计学杂志的副主编。主要研究领域 是生物统计, 计算统计和社会统计。目前的研究方向包括多元零膨胀计数数据分析、斜与非对称连续数据分析, (0, 1) 区间上连续比率数据(以及其推广, 即成份数据)的统计分析, 不完全分类数据分析, 和大维随机矩阵的理论方法及应用。
