Conference on resampling methods and high dimensional data

该项目的重点是组织一个为期两天的国际会议，题为会议上的reservation方法和高维数据在得克萨斯州A M大学，学院站，得克萨斯州，2010年3月25日至26日。会议提供了一个独特的平台，汇集了研究人员在当前统计研究的两个前沿领域，即复杂数据结构的恢复方法和高维数据的推理，以促进对这两个主题的研究思想的交流，并进一步发展这些蓬勃发展的领域。会议由国家统计科学研究所和美国统计协会非参数统计科共同主办。该会议设有一个国际项目委员会，由SN教授担任主席Lahiri教授（得克萨斯A M），以及一个咨询委员会，由R. J.卡罗尔教授（得克萨斯A M），布拉德利埃夫隆教授（斯坦福大学）和汉斯R. Küunsch（ETH，苏黎世，瑞士）。为期两天的会议，会议上的再分配方法和高维数据汇集了顶级和初级研究人员，以确定和扩大两个高度活跃的研究领域的统计和概率，处理复杂的数据结构的研究前沿。有许多科学和工程领域，如生物信息学，脑成像，计量经济学，电气工程，金融，气象学等，这些数据经常出现，并直接受益于这些主题的进展。该基金为选定的与会者群体提供支持，包括研究生、少数民族和无法参加会议的年轻研究人员，从而促进人力资源开发。

This project focuses on organizing a 2-day international conference entitled Conference on resampling methods and high dimensional data at the Texas A & M university, College Station, TX, March 25-26, 2010. The conference provides a unique platform for bringing together researchers working in two cutting edge areas of current research in statistics, namely, Resampling methods for complex data structures and Inference for high dimensional data, in order to facilitate the exchange of research ideas on the two topics and to further the development of these booming fields. The meeting is co-sponsored by the National Institute of Statistical Sciences and by the Section on Nonparametric Statistics, American Statistical Association. The conference has an international program committee chaired by Professors S.N. Lahiri (Texas A & M), and an Advisory Committee, consisting of Professors R.J. Carroll (Texas A & M), Bradley Efron (Stanford), and Hans R. K¨unsch (ETH, Zurich, Switzerland).The two-day conference Conference on resampling methods and high dimensional data brings together top and junior researchers to define and expand the research frontiers of two highly active research areas of statistics and probability that deal with complex data structures. There are a number of areas of science and engineering, such as bio-informatics, brain imaging, econometrics,electrical engineering, finance, meteorology, etc., where such data appear frequently and which directly benefit from advances in these topics. The funding provides support for selected groups of participants including graduate students, minorities, and young researchers who can not attend the conference otherwise, thereby promoting human resource development.