应beat365官方网站的邀请，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：

    时间：5月4日下午16:00-17:00

    地点：理科楼407

    题目：A Functional Varying-Coefficient Single-Index Model for Functional Response Data

    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.

    报告人简介：栗家量 博士，现为新加坡国立大学副教授，主要研究领域为非参数统计、函数型数据分析、高维统计推断等，已发表包含Journal of the Royal Statistical Society Series B, Annals of Statistics, Journal of the American Statistical Association等顶级期刊在内的论文60余篇，目前担任Biometrics, Lifetime Data Analysis等国际权威期刊的Associate Editor。

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