Pub Date : 2024-08-22DOI: 10.1080/01621459.2024.2392906
Ankit Pensia, Varun Jog, Po-Ling Loh
We study the problem of linear regression where both covariates and responses are potentially (i) heavy-tailed and (ii) adversarially contaminated. Several computationally efficient estimators have...
{"title":"Robust regression with covariate filtering: Heavy tails and adversarial contamination","authors":"Ankit Pensia, Varun Jog, Po-Ling Loh","doi":"10.1080/01621459.2024.2392906","DOIUrl":"https://doi.org/10.1080/01621459.2024.2392906","url":null,"abstract":"We study the problem of linear regression where both covariates and responses are potentially (i) heavy-tailed and (ii) adversarially contaminated. Several computationally efficient estimators have...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142276072","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}
Pub Date : 2024-08-22DOI: 10.1080/01621459.2024.2392904
A. Godichon-Baggioni, D. Nguyen, M-N. Tran
This paper introduces a method for efficiently approximating the inverse of the Fisher information matrix, a crucial step in achieving effective variational Bayes inference. A notable aspect of our...
{"title":"Natural Gradient Variational Bayes without Fisher Matrix Analytic Calculation and Its Inversion","authors":"A. Godichon-Baggioni, D. Nguyen, M-N. Tran","doi":"10.1080/01621459.2024.2392904","DOIUrl":"https://doi.org/10.1080/01621459.2024.2392904","url":null,"abstract":"This paper introduces a method for efficiently approximating the inverse of the Fisher information matrix, a crucial step in achieving effective variational Bayes inference. A notable aspect of our...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235080","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}
Pub Date : 2024-08-19DOI: 10.1080/01621459.2024.2392903
Xianru Wang, Bin Liu, Xinsheng Zhang, Yufeng Liu
Data heterogeneity is a challenging issue for modern statistical data analysis. There are different types of data heterogeneity in practice. In this paper, we consider potential structural changes ...
{"title":"Efficient Multiple Change Point Detection and Localization For High-dimensional Quantile Regression with Heteroscedasticity","authors":"Xianru Wang, Bin Liu, Xinsheng Zhang, Yufeng Liu","doi":"10.1080/01621459.2024.2392903","DOIUrl":"https://doi.org/10.1080/01621459.2024.2392903","url":null,"abstract":"Data heterogeneity is a challenging issue for modern statistical data analysis. There are different types of data heterogeneity in practice. In this paper, we consider potential structural changes ...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245505","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}
Pub Date : 2024-08-14DOI: 10.1080/01621459.2024.2388909
Rupam Bhattacharyya, Nicholas C. Henderson, Veerabhadran Baladandayuthapani
Rapid advancements in collection and dissemination of multi-platform molecular and genomics data has resulted in enormous opportunities to aggregate such data in order to understand, prevent, and t...
多平台分子和基因组学数据收集与传播的快速发展为汇总这些数据以了解、预防和治疗疾病带来了巨大的机遇。
{"title":"Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data","authors":"Rupam Bhattacharyya, Nicholas C. Henderson, Veerabhadran Baladandayuthapani","doi":"10.1080/01621459.2024.2388909","DOIUrl":"https://doi.org/10.1080/01621459.2024.2388909","url":null,"abstract":"Rapid advancements in collection and dissemination of multi-platform molecular and genomics data has resulted in enormous opportunities to aggregate such data in order to understand, prevent, and t...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141998732","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}
Pub Date : 2024-08-14DOI: 10.1080/01621459.2024.2388908
Mohamad Elmasri
Bayesian inference for undirected graphical models is mostly restricted to the class of decomposable graphs, as they enjoy a rich set of properties making them amenable to high-dimensional problems...
{"title":"Parallel sampling of decomposable graphs using Markov chains on junction trees","authors":"Mohamad Elmasri","doi":"10.1080/01621459.2024.2388908","DOIUrl":"https://doi.org/10.1080/01621459.2024.2388908","url":null,"abstract":"Bayesian inference for undirected graphical models is mostly restricted to the class of decomposable graphs, as they enjoy a rich set of properties making them amenable to high-dimensional problems...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141998698","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}
Pub Date : 2024-08-13DOI: 10.1080/01621459.2024.2388903
Zheng Tracy Ke, Jingming Wang
Real networks often have severe degree heterogeneity, with maximum, average, and minimum node degrees differing significantly. This paper examines the impact of degree heterogeneity on statistical ...
{"title":"Optimal Network Membership Estimation under Severe Degree Heterogeneity","authors":"Zheng Tracy Ke, Jingming Wang","doi":"10.1080/01621459.2024.2388903","DOIUrl":"https://doi.org/10.1080/01621459.2024.2388903","url":null,"abstract":"Real networks often have severe degree heterogeneity, with maximum, average, and minimum node degrees differing significantly. This paper examines the impact of degree heterogeneity on statistical ...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986515","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}
Pub Date : 2024-07-23DOI: 10.1080/01621459.2024.2382435
Biao Cai, Emma Jingfei Zhang, Hongyu Li, Chang Su, Hongyu Zhao
There is a growing interest in cell-type-specific analysis from bulk samples with a mixture of different cell types. A critical first step in such analyses is the accurate estimation of cell-type p...
{"title":"Statistical Inference of Cell-type Proportions Estimated from Bulk Expression Data","authors":"Biao Cai, Emma Jingfei Zhang, Hongyu Li, Chang Su, Hongyu Zhao","doi":"10.1080/01621459.2024.2382435","DOIUrl":"https://doi.org/10.1080/01621459.2024.2382435","url":null,"abstract":"There is a growing interest in cell-type-specific analysis from bulk samples with a mixture of different cell types. A critical first step in such analyses is the accurate estimation of cell-type p...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141764411","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}
Pub Date : 2024-07-17DOI: 10.1080/01621459.2024.2380105
Jungjun Choi, Ming Yuan
This paper develops an inferential framework for matrix completion when missing is not at random and without the requirement of strong signals. Our development is based on the observation that if t...
{"title":"Matrix Completion When Missing Is Not at Random and Its Applications in Causal Panel Data Models*","authors":"Jungjun Choi, Ming Yuan","doi":"10.1080/01621459.2024.2380105","DOIUrl":"https://doi.org/10.1080/01621459.2024.2380105","url":null,"abstract":"This paper develops an inferential framework for matrix completion when missing is not at random and without the requirement of strong signals. Our development is based on the observation that if t...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730625","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}
Pub Date : 2024-07-09DOI: 10.1080/01621459.2024.2376285
Simeng Shao, Jacob Bien, Adel Javanmard
In many domains, data measurements can naturally be associated with the leaves of a tree, expressing the relationships among these measurements. For example, companies belong to industries, which i...
{"title":"Controlling the False Split Rate in Tree-Based Aggregation","authors":"Simeng Shao, Jacob Bien, Adel Javanmard","doi":"10.1080/01621459.2024.2376285","DOIUrl":"https://doi.org/10.1080/01621459.2024.2376285","url":null,"abstract":"In many domains, data measurements can naturally be associated with the leaves of a tree, expressing the relationships among these measurements. For example, companies belong to industries, which i...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602711","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}
Pub Date : 2024-07-08DOI: 10.1080/01621459.2024.2375035
Reza Mohammadi
Published in Journal of the American Statistical Association (Just accepted, 2024)
发表于《美国统计协会期刊》（刚刚接受，2024 年）
{"title":"Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests","authors":"Reza Mohammadi","doi":"10.1080/01621459.2024.2375035","DOIUrl":"https://doi.org/10.1080/01621459.2024.2375035","url":null,"abstract":"Published in Journal of the American Statistical Association (Just accepted, 2024)","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597507","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}
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