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20181226 Sai Li: High-Dimensional inference: Debiasing the debiased Lasso with bootstrap
时间:2018-12-20

报告时间20181226 14:0015:00

报告地点:明德主楼1016会议室

报告题目: High-Dimensional inference: Debiasing the debiased Lasso with bootstrap


报告摘要:

In this talk, we consider the problem of constructing confidence intervals for low-dimensional coefficients in high-dimensional linear regression models. We propose to further debias the debiased Lasso estimator with bootstrap and prove its consistency for distribution approximation under proper conditions. The proposed method admits weaker sample size conditions in existence of a large proportion of large coefficients and reveals the benefits of having strong signals.


报告人简介

  Sai Li is currently a postdoctoral researcher at Biostatistics Department of University of Pennsylvania. She received her PhD degree from Department of Statistics and Biostatistics at Rutgers University in 2018. Her research interests include high-dimensional statistics, bootstrap, and instrumental variable analysis.