学术报告
主讲内容：Multivariate Max-Stable Processes for Extreme Values
主讲 人： Professor Huiyan Sang
Texas A&M University
时 间：6月14日（星期三）上午10：00
地 点：统计研究院426教室
Abstract:
Analysis of spatial extremes are currently based on univariate processes. Max-stable processes allow to model and explicitly quantify the spatial dependence of extremes, therefore they are widely adopted in the applications. For a better understanding of extreme events of real processes,such as environmental phenomena, it may be useful to simultaneously study several spatialvariables. To this end, we extend some theoretical results and applications of max-stable processes
to the multivariate setting to analyze extreme events of several variables observed acrossspace. In particular, we study the maxima of independent replicates of multivariate processes,both in the Gaussian and Student-t cases. Then, we define a Poisson process construction in themultivariate setting and introduce multivariate versions of the Smith Gaussian extreme-value, theSchlather extremal-Gaussian and extremal-t, and the Brown–Resnick models. Inferential aspectsfor those models based on composite likelihoods are developed. We show the results of variousMonte Carlo simulations and of an application to a dataset of monthly wind speed and wind gust in Oklahoma, U.S.A., highlighting the utility of working with multivariate models in contrast to the univariate case.
Short Bio of Professor Huiyan Sang
Dr. Huiyan Sang received her Ph.D in Statistics from Duke University in 2008, and B.S. in Mathematics and Applied Mathematics from Peking University, China, in 2004. She joined the faculty at Texas A&M University in 2008, where she is currently an Associate Professor in the Department of Statistics. Her research focuses on spatial statistics, extreme values and computational methods for large datasets.
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统计研究院
2017年5月28日