科研交流
您的位置>>首页 > 科研交流 > 学术交流 > 阅读正文
科研交流

数学学院、所系列学术报告(720场):加拿大湖首大学 李德立教授

admin 发表于: 2017-07-10 10:16  点击:506

  目:A Central Limit Theorem for Bootstrap Sample Sums from Non-I.I.D. Models

报告人:加拿大湖首大学 李德立教授

  间:2017721  13:30-14:30

  点:数学楼一楼报告厅

 

摘要:For bootstrap sample sums resulting from a sequences of random variables {}, a very general central limit theorem is established. The random variables {} do not need to be independent or identically distributed or to be of any particular dependence structure. Furthermore, no conditions, including moment conditions, are imposed in general on the marginal distributions of the {}. As a special case of the main result, a result of Liu (1988) concerning independent but not identically distributed {} is extended to a larger class of parent sequences.

This work has been published in Journal of Statistical Planning and Inference 180(2017), 69-80.