时 间：2025年5月9 日（周五）13：30 -14：30
地 点：理科大楼A614室
报告人：肖益民 密歇根州立大学(Michigan State University) 教授
主持人：李育强 华东师范大学教授
摘 要：
In recent years, a number of classes of new multivariate random fields have been constructed by using various approaches (e.g., covariance matrices, variogram matrices, spectral representations, systems of stochastic partial differential equations) and have been applied for modeling multivariate spatial data or for computer experiments. In this talk, we provide an overview on several classes of multivariate Gaussian random fields including multivariate Matern Gaussian fields and operator fractional Brownian motions, and vector-valued operator-scaling random fields, and present some recent results on estimation, prediction, and computer experiments of bivariate Gaussian random fields. These results illustrate explicitly the effects of the dependence structures among the coordinate processes on statistical analysis and computer experiments of multivariate Gaussian random field models.
报告人简介：
肖益民教授是密西根州立大学统计概率系终身教授，2018年成为密西根州立大学Research Foundation Professor。2011年当选为美国数理统计学会会士。主要从事随机场及随机偏微分方程，分形几何，随机场的极值理论,空间统计,非参数估计方面的研究。在国际知名数学和统计杂志发表学术论文160余篇。