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“創(chuàng)源”大講堂研究生學(xué)術(shù)講座

報(bào)告人：王啟華，中國科學(xué)院研究員, 博士生導(dǎo)師

講座題目：How to make model-free feature screening approaches for full data applicable  

                             to missing response case?

講座時(shí)間：2015年5月28日（周四）下午14：00～15：00

講座地點(diǎn)：犀浦校區(qū)kaiyun開云官方網(wǎng)站報(bào)告廳X2511

報(bào)告內(nèi)容：Abstarct: It is quite challenge to develop model-free feature screening approaches {\it directly} for missing response problems since the existing standard missing data analysis methods cannot be applied directly to high dimensional case. This paper develops a novel technique by borrowing information of missingness indicators such that any feature screening procedures for ultrahigh-dimensional covariates with full data can be applied to missing response case. This technique is developed by proving that the set of the active predictors on the response is a subset of the active predictors on the product of the response and missingness indicator. Then, any standard model-free feature screening procedures with screening property for full data can be applied to estimating the latter one. Hence, the probability that the estimated set contains the set of the latter one and hence the previous one tends to one. It is shown that the complete case (CC) approach can also keep the feature screening property of any feature screening approach with feature screening property for full data. As an alternative, a two-step approach is also developed for obtaining a feature screening estimator of the active predictor set of interest. A simulation study was conducted to compare the proposed methods with the ``complete case" (CC) approach. Real data analysis was used to illustrate the proposed method. Both the simulation studies and real data analysis indicate that the proposed zero imputation feature screening method outperforms the CC method and the two step one.

個(gè)人簡介：

王啟華，中國科學(xué)院研究員, 博士生導(dǎo)師, 國家杰出青年基金獲得者, 教育部長江學(xué)者獎(jiǎng)勵(lì)計(jì)劃特聘教授, 中國科學(xué)院“百人計(jì)劃”入選者，國際統(tǒng)計(jì)研究會(huì)推選會(huì)員（Elected member of the International Statistical Institute (ISI)）。 研究興趣是生存分析、缺失數(shù)據(jù)分析、半-非參數(shù)統(tǒng)計(jì)推斷、高維數(shù)據(jù)統(tǒng)計(jì)分析，發(fā)表論文百余篇，其中在美國統(tǒng)計(jì)學(xué)會(huì)雜志（JASA），統(tǒng)計(jì)年鑒 （Ann. Statist.），Biometrik等國際重要刊物發(fā)表論文80余篇。是一些國際國內(nèi)刊物的編委。先后訪問香港科技大學(xué)、美國加州大學(xué)戴維斯分校，美國加州大學(xué)洛杉磯分校、美國耶魯大學(xué)、美國西雅圖華盛頓大學(xué)、加拿大卡爾頓大學(xué)、德國洪堡大學(xué)及澳大利亞國立大學(xué)等。

主辦：研究生院

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