Estimation of Proportion of Null Hypotheses Under Dependence

Nabaneet Das
{"title":"Estimation of Proportion of Null Hypotheses Under Dependence","authors":"Nabaneet Das","doi":"arxiv-2409.04100","DOIUrl":null,"url":null,"abstract":"Estimation of the proportion of null hypotheses in a multiple testing problem\ncan greatly enhance the performance of the existing algorithms. Although\nvarious estimators for the proportion of null hypotheses have been proposed,\nmost are designed for independent samples, and their effectiveness in dependent\nscenarios is not well explored. This article investigates the asymptotic\nbehavior of the BH estimator and evaluates its performance across different\ntypes of dependence. Additionally, we assess Storey's estimator and another\nestimator proposed by Patra and Sen (2016) to understand their effectiveness in\nthese settings.","PeriodicalId":501379,"journal":{"name":"arXiv - STAT - Statistics Theory","volume":"24 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Statistics Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.04100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Estimation of the proportion of null hypotheses in a multiple testing problem can greatly enhance the performance of the existing algorithms. Although various estimators for the proportion of null hypotheses have been proposed, most are designed for independent samples, and their effectiveness in dependent scenarios is not well explored. This article investigates the asymptotic behavior of the BH estimator and evaluates its performance across different types of dependence. Additionally, we assess Storey's estimator and another estimator proposed by Patra and Sen (2016) to understand their effectiveness in these settings.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
依赖性条件下的零假设比例估计
在多重检验问题中,估计无效假设的比例可以大大提高现有算法的性能。虽然已经提出了各种无效假设比例估计器,但大多数估计器都是针对独立样本设计的,它们在依赖样本情况下的有效性还没有得到很好的探讨。本文研究了 BH 估计器的渐近行为,并评估了它在不同依赖类型中的性能。此外,我们还评估了 Storey 估计器和 Patra 和 Sen(2016 年)提出的另一种估计器,以了解它们在这些情况下的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Cyclicity Analysis of the Ornstein-Uhlenbeck Process Linear hypothesis testing in high-dimensional heteroscedastics via random integration Asymptotics for conformal inference Sparse Factor Analysis for Categorical Data with the Group-Sparse Generalized Singular Value Decomposition Incremental effects for continuous exposures
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1