讲座题目：Statistical Inference for High-dimensional Data
主 讲 人：张新生 复旦大学管理学院统计系主任，教授，博士生导师
时 间：11月24日（周五）下午2:30
地 点：燕山校区四号教学楼六层法学院报告厅
主讲人人简介：
张新生，复旦大学管理学院统计系主任，教授，博士生导师。张新生教授博士毕业于北京师范大学，师从中国概率论研究的先驱王梓坤院士。张新生教授主要从事过程统计、MCMC与Bayes统计分析、随机序与风险管理以及高维统计等方面的研究，在国内外概率统计权威期刊发表50余篇论文，主持多项国家自然科学基金，并担任上海市数学会常务理事。
报告摘要:
In the last decades, high-dimensional data analysis has been an active area. Methodology for the analysis of high-dimensional data is one of the most important research topics in statistics. For high-dimensional data, the number of explanatory variables is much larger than the sample size. The conventional methods of statistical inference are no longervalid. In this talk I will briefly review recent development on the statistical methodology and theory for the analysis of high-dimensional data. I will also introduce our recentresults on the comparison of Kendall's tau matrix from two independent populations under the high-dimensional setting.
