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bat365在线平台、所2020年系列学术活动(第54场):严晓东 副研究员 山东大学

发表于: 2021-05-31   点击: 

报告题目:High-dimensional Integrative Analysis for Heterogeneous Stratified Model

报告人:严晓东 副研究员 山东大学

报告时间:2021年6月10日 14:00-15:00

报告地点:腾讯会议 会议 ID:295 560 073   会议密码:0610

校内联系人:王培洁 wangpeijie@jlu.edu.cn


报告摘要:In modern economic studies, the population heterogeneity of multiple stratifications and the high dimensionality of the predictors pose a major challenge. In this study, we introduce an integrative procedure that can be used to explore the information regarding group and sparsity structures for high-dimensional and heterogeneous stratified models. Further, we propose $K$-regression modeling as a hybrid of complex and simple models exhibiting arbitrary dependence on the stratification features, but linear dependence on other variables. $K$-regression models preeminently exhibit the following features:(i) they are essentially non-parametric with respect to the stratified feature, and parametric linearly effects in other variables with potentially integrative pattern because the effects and the corresponding sparsity structures can be the same for the stratifications in common groups but vary across different groups; (ii) the devised $K$-regression algorithm can automatically integrate the stratifications pertaining to common regression model and simultaneously estimate the corresponding effects simultaneously; (iii) the proposal quickly recovers the subpopulation and sparsity structure of the $K$-regression models within massive and high-dimensional stratifications; (iv) the resulting estimators exhibit two-layer oracle properties, i.e., the oracle estimator obtained using the known group and sparsity structures is the local minimizer of the objective function with high probability. The stratification-specific bootstrap (SSB) sampling scheme was developed to improve the integration accuracy. Furthermore, the simulation studies provide supportive evidence  that the newly proposed method performs appropriately in case of finite samples; a real data example has been provided for illustration.


报告人简介:严晓东,山东大学未来学者,山东大学金融研究院副研究员,山东大学经济学院杰出青年,博士生导师,云南大学与香港理工大学联合培养博士,香港中文大学研究助理,中国现场统计研究会高维数据统计分会理事,山东省大数据专业建设委员会常务副秘书长,山东省应用统计学会副秘书长,山东省财政厅第一批省级政策性农业保险咨询专家。在国际顶级期刊The Annals of Statistics, Journal of the American Statistical Association,Journal of Econometrics,以及著名期刊International Journal of forecasting, Statistica Sinica,Journal of Multivariate Analysis,Statistics in Medicine等发表论文十余篇。目前主持国家自然科学基金,国家博士后留学基金,山东省自然科学基金、山东省社科规划项目基金、山东省青年学者未来计划基金。