A Functional Varying-Coefficient Single-Index Model for Functional Response Data
讲座名称：
A Functional Varying-Coefficient Single-Index Model for Functional Response Data
讲座时间：
2017-05-04
讲座人：
栗家量
形式：
校区：
兴庆校区
实践学分：
讲座内容：
应数学与统计学院的邀请，新加坡国立大学栗家量副教授将于近期访问我院，并为师生作以下学术报告：
讲座题目：A Functional Varying-Coefficient Single-Index Model for Functional Response Data
讲座时间：5月4日下午16:00-17:00
讲座地点：理科楼407
讲座人：栗家量
讲座摘要：Motivated by the analysis of imaging data, we propose a novel functional varying-coefficient single-index model (FVCSIM) to carry out the regression analysis of functional response data on a set of covariates of interest. FVCSIM represents a new extension of varying-coefficient single-index models for scalar responses collected from cross-sectional and longitudinal studies. An efficient estimation procedure is developed to iteratively estimate varying coefficient functions, link functions, index parameter vectors, and the covariance function of individual functions. We systematically examine the asymptotic properties of all estimators including the weak convergence of the estimated varying coefficient functions, the asymptotic distribution of the estimated index parameter vectors, and the uniform convergence rate of the estimated covariance function and their spectrum. Simulation studies are carried out to assess the finite-sample performance of the proposed procedure. We apply FVCSIM to investigate the development of white matter diffusivities along the corpus callosum skeleton obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. Supplementary material for this article is available online.
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