发布求助
文献互助 智能选刊 最新文献

Journal of the American Statistical Association最新文献

筛选
英文 中文
Mediation analysis with the mediator and outcome missing not at random 调解人和结果非随机缺失的调解分析
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-05-28 DOI: 10.1080/01621459.2024.2359132
Shuozhi Zuo, Debashis Ghosh, Peng Ding, Fan Yang
{"title":"Mediation analysis with the mediator and outcome missing not at random","authors":"Shuozhi Zuo, Debashis Ghosh, Peng Ding, Fan Yang","doi":"10.1080/01621459.2024.2359132","DOIUrl":"https://doi.org/10.1080/01621459.2024.2359132","url":null,"abstract":"Mediation analysis is widely used for investigating direct and indirect causal pathways through which an effect arises. However, many mediation analysis studies are challenged by missingness in the...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"53 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Population-level Balance in Signed Networks 签名网络中人口层面的平衡
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-05-21 DOI: 10.1080/01621459.2024.2356894
Weijing Tang, Ji Zhu
{"title":"Population-level Balance in Signed Networks","authors":"Weijing Tang, Ji Zhu","doi":"10.1080/01621459.2024.2356894","DOIUrl":"https://doi.org/10.1080/01621459.2024.2356894","url":null,"abstract":"Statistical network models are useful for understanding the underlying formation mechanism and characteristics of complex networks. However, statistical models for signed networks have been largely...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"17 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Doubly Robust Augmented Model Accuracy Transfer Inference with High Dimensional Features 具有高维特征的双稳健增强模型精度转移推理
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-05-21 DOI: 10.1080/01621459.2024.2356291
Doudou Zhou, Molei Liu, Mengyan Li, Tianxi Cai
{"title":"Doubly Robust Augmented Model Accuracy Transfer Inference with High Dimensional Features","authors":"Doudou Zhou, Molei Liu, Mengyan Li, Tianxi Cai","doi":"10.1080/01621459.2024.2356291","DOIUrl":"https://doi.org/10.1080/01621459.2024.2356291","url":null,"abstract":"Transfer learning is crucial for training models that generalize to unlabeled target populations using labeled source data, especially in real-world studies where label scarcity and covariate shift...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"2 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle 利用 Muscle 对单细胞三维基因组和表观遗传数据进行联合张量建模
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-05-21 DOI: 10.1080/01621459.2024.2358557
Kwangmoon Park, Sündüz Keleş
{"title":"Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle","authors":"Kwangmoon Park, Sündüz Keleş","doi":"10.1080/01621459.2024.2358557","DOIUrl":"https://doi.org/10.1080/01621459.2024.2358557","url":null,"abstract":"Emerging single cell technologies that simultaneously capture long-range interactions of genomic loci together with their DNA methylation levels are advancing our understanding of three-dimensional...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"28 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Rational Kriging 理性克里金法
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-05-20 DOI: 10.1080/01621459.2024.2356296
V. Roshan Joseph
{"title":"Rational Kriging","authors":"V. Roshan Joseph","doi":"10.1080/01621459.2024.2356296","DOIUrl":"https://doi.org/10.1080/01621459.2024.2356296","url":null,"abstract":"This article proposes a new kriging that has a rational form. It is shown that the generalized least squares estimator of the mean from rational kriging is much more well behaved than that of ordin...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"4 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141308977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Neural networks for geospatial data 用于地理空间数据的神经网络
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-05-20 DOI: 10.1080/01621459.2024.2356293
Wentao Zhan, Abhirup Datta
{"title":"Neural networks for geospatial data","authors":"Wentao Zhan, Abhirup Datta","doi":"10.1080/01621459.2024.2356293","DOIUrl":"https://doi.org/10.1080/01621459.2024.2356293","url":null,"abstract":"Abstract–Analysis of geospatial data has traditionally been model-based, with a mean model, customarily specified as a linear regression on the covariates, and a Gaussian process covariance model, ...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"123 4 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Tests for large-dimensional shape matrices via Tyler’s M estimators 通过泰勒 M 估计数测试大维度形状矩阵
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-05-03 DOI: 10.1080/01621459.2024.2350573
Runze Li, Weiming Li, Qinwen Wang
{"title":"Tests for large-dimensional shape matrices via Tyler’s M estimators","authors":"Runze Li, Weiming Li, Qinwen Wang","doi":"10.1080/01621459.2024.2350573","DOIUrl":"https://doi.org/10.1080/01621459.2024.2350573","url":null,"abstract":"Tyler’s M estimator, as a robust alternative to the sample covariance matrix, has been widely applied in robust statistics. However, classical theory on Tyler’s M estimator is mainly developed in t...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"13 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140845366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Controlled Discovery and Localization of Signals via Bayesian Linear Programming 通过贝叶斯线性规划控制信号的发现和定位
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-04-26 DOI: 10.1080/01621459.2024.2347667
Asher Spector, Lucas Janson
{"title":"Controlled Discovery and Localization of Signals via Bayesian Linear Programming","authors":"Asher Spector, Lucas Janson","doi":"10.1080/01621459.2024.2347667","DOIUrl":"https://doi.org/10.1080/01621459.2024.2347667","url":null,"abstract":"Scientists often must simultaneously localize and discover signals. For instance, in genetic fine-mapping, high correlations between nearby genetic variants make it hard to identify the exact locat...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"6 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140648953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Estimating trans-ancestry genetic correlation with unbalanced data resources 利用不平衡数据资源估算跨宗族遗传相关性
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-04-19 DOI: 10.1080/01621459.2024.2344703
Bingxin Zhao, Xiaochen Yang, Hongtu Zhu
{"title":"Estimating trans-ancestry genetic correlation with unbalanced data resources","authors":"Bingxin Zhao, Xiaochen Yang, Hongtu Zhu","doi":"10.1080/01621459.2024.2344703","DOIUrl":"https://doi.org/10.1080/01621459.2024.2344703","url":null,"abstract":"The aim of this paper is to propose a novel method for estimating trans-ancestry genetic correlations in genome-wide association studies (GWAS) using genetically-predicted observations. These corre...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"76 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140620558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Modeling and Learning on High-Dimensional Matrix-Variate Sequences 高维矩阵变量序列的建模与学习
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-04-19 DOI: 10.1080/01621459.2024.2344687
Xu Zhang, Catherine C. Liu, Jianhua Guo, K. C. Yuen, A. H. Welsh
{"title":"Modeling and Learning on High-Dimensional Matrix-Variate Sequences","authors":"Xu Zhang, Catherine C. Liu, Jianhua Guo, K. C. Yuen, A. H. Welsh","doi":"10.1080/01621459.2024.2344687","DOIUrl":"https://doi.org/10.1080/01621459.2024.2344687","url":null,"abstract":"We propose a new matrix factor model, named RaDFaM, which is strictly derived based on the general rank decomposition and assumes a structure of a high-dimensional vector factor model for each basi...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"33 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140620560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页 下一页 尾页
0
×
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
请完成安全验证×
相关产品
×
本文献相关产品
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信