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  • 统计与管理学院2017年学术报告第54

     

    【主  题】Variable Selection Procedure From Multiple Testing

    【报告人】张宝学

              首都经济贸易大学统计学院教授

    【时  间】 2017年8月18日(星期五)15:15-16:00

    【地  点】 上海财经大学统计与管理学院大楼1316室

    【摘 要】Variable selection plays an important role in statistical learning and scientific discoveries during the past ten years and multiple testing is a fundamental problem in statistical inference, also with wide applications in many scientific fields. Significant advances have been achieved in both two areas, respectively. This paper aims at figuring out a connection between the adaptive lasso and multiple testing procedure in linear regression models, and also aims at proposing procedures

    based on the multiple testing methods to select variables and control the selecting error rate which is called false discovery rate. Simulation studies show good performance of the proposed methods on controlling the selecting error rate and achieving great powers in a wide range of settings.