2019年研究生学术前沿讲座(23)-Oracally Efficient Estimation and Simultaneous Inference in Partially Linear Single-index Models for Longitudinal Data

2019年研究生学术前沿讲座(23

 

人:王所进  教授  德克萨斯A&M大学

主题名称:Oracally Efficient Estimation and Simultaneous Inference in Partially Linear Single-index Models for Longitudinal Data

简要内容:

    In this presentation, we discuss oracally efficient estimation and asymptotically accurate simultaneous confidence band (SCB) for the nonparametric link function in the partially linear single-index models for longitudinal data. The proposed procedure works for possibly unbalanced longitudinal data under general conditions. The link function estimator is shown to be oracally efficient in the sense that it is asymptotically equivalent in the order of one over root n to that with all true values of the parameters being known oracally. Furthermore, the asymptotic distribution of the maximal deviation between the estimator and the true link function is provided, and hence an SCB for the link function is constructed. Finite sample simulation studies are carried out which support our asymptotic theory. The proposed SCB is applied to analyze a CD4 data set. 

 

时间地点:2019620日下午300-430   地点:经济管理学院335

主办学院:经济管理学院

 

  

365足球外围平台

2019.5.30

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