主  題：Variable Selection Procedure From Multiple Testing

內(nèi)容簡(jiǎn)介：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.

報(bào)告人：張寶學(xué)      教授    博導(dǎo)
時(shí)  間：2017-09-01    16:00

地  點(diǎn)：競(jìng)慧東樓302

舉辦單位：理學(xué)院  統(tǒng)計(jì)科學(xué)與大數(shù)據(jù)研究院、  科研部