报告时间：2024年08月04日（星期日）10:00-11:00

报告地点：科教楼B座1710

报告人：肖益民 教授

工作单位：Michigan State University

举办单位：金沙集团1862cc成色

报告简介：

In recent years, a number of classes of new multivariate randomfields have been constructedby using the approaches of covariance matrices, variogram matrices, the convolution method,spectral representations, or systems of stochastic partial differential equations (SPDEs), andhave been applied for modeling multivariate spatial data. However, the theoretical developmentof parameter estimation, prediction, and extreme values for multivariate randomfields is stillunder-developed and the range of their applications is growing constantly.

In this talk, we provide an overview on several classes of multivariate Gaussian randomfields including multivariate Matern Gaussianfields, operator fractional Brownian motion,and matrix-valued Gaussian randomfields, and some recent results on estimation and prediction of bivariate Gaussian randomfields. These results illustrate explicitly the effects of thedependence structures among the coordinate processes on statistical analysis of multivariateGaussian randomfields.

报告人简介：

肖益民教授，Department Statistics and Probability, Michigan State University,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，位势理论，随机场的极值理论，空间统计，非参数估计方面的研究，并取得了一系列具有国际先进水平的重要成果，在国际知名数学和统计杂志发表学术论文150余篇，在数十种主要国际会议上做大会专题发言；自1998年至今，主持或共同主持美国国家自然科学基金项目十三项。曾担任SCI杂志《Statistics and Probability Letters》（统计和概率通讯）共同主编（2011-2022），现担任《Science in China, Mathematics》（中国科学，数学），《Illinois Journal of Mathematics》（伊利诺伊数学杂志）《Journal of Fractal Geometry》（分形几何杂志）的编委。多次担任美国国家自然科学基金概率和统计项目评审小组成员，以及加拿大，瑞士，德国，香港等国家和地区自然科学基金评审人。在Annals of Probability，Probability Theory and Related Fields,Journal of Theoretical Probability,Electronic Journalof Probability,Bernoulli,Annalsof Applied Probability,Journalof Differential Equations,Journal Of Mathematical Analysis And Applications, Statistics and Probability Letters等国际一流期刊发表论文。

主要的研究领域：Stochastic Processes and Random Fields (Gaussian randomfields; matrix-valued randomfields; infinitely divisible randomfields; Levy processes; and Markov processes);Stochastic Partial Differential Equations；Statistical Analysis of Random Field Models (Estimation and prediction);Extreme Value Theory;Random Fractals, Geometry of Fractals.