报告题目: Two-sample Functional Linear Models
报 告 人: 张日权教授（华东师范大学统计学院）
报告时间: 2018年9月27日(周四) 下午 16:30-17:30
报告摘要：In this report we study two-sample functional linear regression with a scaling transformation of regression functions. We consider estimation for the intercept, the slope function and the scalar parameter based on the functional principal component analysis. We also establish the rates of convergence for the estimator of the slope function, which is shown to be optimal in a minimax sense under certain smoothness assumptions. We further investigate semi-parametric efficiency for the estimation of the scalar parameter and hypothesis testing. We also extend the proposed method to sparsely and irregularly sampled functional data and establish the consistency for the estimators of the scalar and the slope function. We evaluate numerical performance of the proposed methods through simulation studies and illustrate their utility via analysis of an AIDS data set.