※ [本文转录自 NCTU-STAT98G 看板 #1Clo9YsK ] 作者: missergirl (猫猫) 看板: NCTU-STAT98G 标题: [演讲公告] 10/22 统计所专题演讲 时间: Thu Oct 21 01:09:49 2010 交通大学、清华大学 统计学研究所 专题演讲 题　目：A Two-Stage Dimension Reduction Method for Induced Response and Its Applications 主讲人：洪弘教授 (台湾大学流行病学与预防医学研究所) 时　间：99年10月22日(星期五)上午10:40-11:30 (上午10:20-10:40茶会於交大统计所429室举行) 地　点：交大综合一馆427室 Abstract Researches nowadays usually encounter the curse of high-dimensionality where many developed statistical models fail to overcome. To tackle this problem, suffcient dimension reduction aims to search the central subspace (CS) in which necessary information of covariates regarding response are contained. Subsequent statistical analysis can then be implemented in a low-dimensional space while preserving relevant information. Several studies are interested in certain transformation of the response (the induced response) instead of the original one. With dfferent transformations under consideration, the corresponding CS may vary. When estimating this induced central subspace (ICS), existing dimension reduction methods, however, may suffer the problem of ineffciency. In this article, we propose a more effcient two-stage estimation procedure to estimate the ICS. This approach is further extended to the case of censored response. An application to combining multiple biomarkers is also illustrated. Simulation studies and two data examples, the Cardiac Arrhythmia Study and the Angiography Cohort Study, evidence the usefulness of our method. --

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