科学研究
学术报告
A Central Limit Theorem for Bootstrap Sample Sums from Non-I.I.D. Models
发布时间:2017-06-19浏览次数:

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

报告人:Professor Deli Li (加拿大Lakehead大学数学科学系教授)

地点:致远楼102室

时间:2017年6月19日(周一)下午15:30开始

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.

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