报告人：Liuhua Peng (University of Melbourne)
时间：2018-11-28 09:30-10:20
地点：Room 1304, Sciences Building No. 1
Abstract: This project studies distributed statistical inference for a general type of statistics that
encompasses U-statistics and M-estimator in the context of massive data. When the data are stored
on multiple platforms, it is usually expensive and slow to do data communication. To deal with
this issue, we formulate the distributed statistics which can be computed distributively and hence
reduces computational time signicantly. We investigate properties of the distributed statistics from
the perspective of mean square error of estimation and their asymptotic distributions. In addition,
we propose two distributed bootstrap algorithms which are computationally effective and
consistent theoretically. Applications of our approaches and numerical studies are provided to support them.
