Estimations for sparse and irregularly spaced functional data

浙江大学数学科学学院九十周年院庆系列活动之七十五

报告题目：Estimations for sparse and irregularly spaced functional data

报告人：陈迪荣教授

时间与地点：2018年9月29日下午3：00-4:00，工商楼200-9

报告摘要：Classical estimation methods  usually are designed  for densely sampled function data, and do not work well for sparsely and irregularly spaced observations. This talk discusses the estimations of covariance function as well as mean function of functional data. We introduce a framelet based estimation, which are constructed with empirical framelet expression and block thresholding. The asymptotic properties are discussed and some convergence rates are established.