本站大事记   |  收藏本站
高级检索  全文检索  
当前位置:   本站首页   >   讲座预告   >   正文

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

发布日期:2017-07-12      点击:

题 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

时 间:2017年7月21日 13:30-14:30

地 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.

我要评论:
 匿名发布 验证码 看不清楚,换张图片
0条评论    共1页   当前第1

相关文章

  • 读取内容中,请等待...
地址:吉林省长春市前进大街2699号 E-mail:jlunewsnet@163.com
Copyright©2012 All rights reserved. 吉林大学党委宣传部 版权所有

手机版