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An adaptive lack of t test for bigdata

发布时间:2019-03-26     来源:    点击数:
主题: An adaptive lack of t test for bigdata
类型: 学术报告
主办方:
报告人: 王兆军教授(南开大学)
日期: 2018年5月3日9:00-10:00
地点: 知新楼B-1238
内容:

报告题目:An adaptive lack of t test for bigdata

报 告 人:王兆军教授(南开大学)

报告时间:201853日(周四)上午9:00-10:00

报告地点:知新楼B-1238

 

报告摘要:

New technological advancements combinedwith powerful computer hardware and high-speed network make big data available.The massive sample size of big data introduces unique computational challengeson scalability and storage of statistical methods. In this paper, we focus onthe lack of t test of parametric regression models under the framework of bigdata. We develop a computationally feasible testing approach via integratingthe divide and conquer algorithm into a powerful nonparametric test statistic.Our theory results show that under mild conditions the asymptotic nulldistribution of the proposed test is standard normal. Furthermore, the proposedtest benets from the use of data-driven bandwidth procedure and thus possessescertain adaptive property. Simulation studies show that the proposed method hassatisfactory performances, and it is illustrated with an analysis of an airlinedata.

 

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