Pub Date : 2024-11-04DOI: 10.1080/01621459.2024.2423971
Xiucai Ding, Yichen Hu, Zhenggang Wang
In this paper, we propose a new test for testing the equality of two population covariance matrices in the ultra-high dimensional setting that the dimension is much larger than the sizes of both of...
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Pub Date : 2024-11-04DOI: 10.1080/01621459.2024.2423435
P. Richard Hahn
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":"Bayesian Nonparametrics for Causal Inference and Missing Data","authors":"P. Richard Hahn","doi":"10.1080/01621459.2024.2423435","DOIUrl":"https://doi.org/10.1080/01621459.2024.2423435","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":"59 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142589056","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 : 2024-10-25DOI: 10.1080/01621459.2024.2419114
Chanwoo Lee, Miaoyan Wang
We consider the problem of structured tensor denoising in the presence of unknown permutations. Such data problems arise commonly in recommendation systems, neuroimaging, community detection, and m...
{"title":"Statistical and computational efficiency for smooth tensor estimation with unknown permutations","authors":"Chanwoo Lee, Miaoyan Wang","doi":"10.1080/01621459.2024.2419114","DOIUrl":"https://doi.org/10.1080/01621459.2024.2419114","url":null,"abstract":"We consider the problem of structured tensor denoising in the presence of unknown permutations. Such data problems arise commonly in recommendation systems, neuroimaging, community detection, and m...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"3 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142556221","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 : 2024-10-18DOI: 10.1080/01621459.2024.2415719
Cheng Yu, Dong Li, Feiyu Jiang, Ke Zhu
Matrix-variate time series data are largely available in applications. However, no attempt has been made to study their conditional heteroskedasticity that is often observed in economic and financi...
{"title":"Matrix GARCH model: Inference and application*","authors":"Cheng Yu, Dong Li, Feiyu Jiang, Ke Zhu","doi":"10.1080/01621459.2024.2415719","DOIUrl":"https://doi.org/10.1080/01621459.2024.2415719","url":null,"abstract":"Matrix-variate time series data are largely available in applications. However, no attempt has been made to study their conditional heteroskedasticity that is often observed in economic and financi...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"3 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142486731","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 : 2024-10-18DOI: 10.1080/01621459.2024.2412362
Alex Diana, Eleni Matechou, Jim Griffin, Douglas W. Yu, Mingjie Luo, Marie Tosa, Alex Bush, Richard Griffiths
DNA-based biodiversity surveys, which involve collecting physical samples from survey sites and assaying them in the laboratory to detect species via their diagnostic DNA sequences, are increasingl...
{"title":"eDNAPlus: A unifying modelling framework for DNA-based biodiversity monitoring","authors":"Alex Diana, Eleni Matechou, Jim Griffin, Douglas W. Yu, Mingjie Luo, Marie Tosa, Alex Bush, Richard Griffiths","doi":"10.1080/01621459.2024.2412362","DOIUrl":"https://doi.org/10.1080/01621459.2024.2412362","url":null,"abstract":"DNA-based biodiversity surveys, which involve collecting physical samples from survey sites and assaying them in the laboratory to detect species via their diagnostic DNA sequences, are increasingl...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"79 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142556222","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 : 2024-10-15DOI: 10.1080/01621459.2024.2413201
Jinyuan Chang, Qin Fang, Xinghao Qiao, Qiwei Yao
We propose a two-step procedure to model and predict high-dimensional functional time series, where the number of function-valued time series p is large in relation to the length of time series n. ...
我们提出了一个两步程序来模拟和预测高维函数时间序列，其中函数值时间序列的数量 p 相对于时间序列的长度 n 较大。
{"title":"On the Modelling and Prediction of High-Dimensional Functional Time Series","authors":"Jinyuan Chang, Qin Fang, Xinghao Qiao, Qiwei Yao","doi":"10.1080/01621459.2024.2413201","DOIUrl":"https://doi.org/10.1080/01621459.2024.2413201","url":null,"abstract":"We propose a two-step procedure to model and predict high-dimensional functional time series, where the number of function-valued time series p is large in relation to the length of time series n. ...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"8 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142490564","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 : 2024-10-15DOI: 10.1080/01621459.2024.2412364
Xuancheng Wang, Ling Zhou, Huazhen Lin
In this paper, we develop a novel efficient and robust nonparametric regression estimator under a framework of a feedforward neural network (FNN). There are several interesting characteristics for ...
{"title":"Deep regression learning with optimal loss function","authors":"Xuancheng Wang, Ling Zhou, Huazhen Lin","doi":"10.1080/01621459.2024.2412364","DOIUrl":"https://doi.org/10.1080/01621459.2024.2412364","url":null,"abstract":"In this paper, we develop a novel efficient and robust nonparametric regression estimator under a framework of a feedforward neural network (FNN). There are several interesting characteristics for ...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"32 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142589062","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 : 2024-10-15DOI: 10.1080/01621459.2024.2412363
Purevdorj Tuvaandorj
This paper develops permutation versions of identification-robust tests in linear instrumental variables regression. Unlike the existing randomization and rank-based tests in which independence bet...
{"title":"Robust Permutation Tests in Linear Instrumental Variables Regression","authors":"Purevdorj Tuvaandorj","doi":"10.1080/01621459.2024.2412363","DOIUrl":"https://doi.org/10.1080/01621459.2024.2412363","url":null,"abstract":"This paper develops permutation versions of identification-robust tests in linear instrumental variables regression. Unlike the existing randomization and rank-based tests in which independence bet...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"106 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142448730","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}
Forecasts of regional electricity net-demand, consumption minus embedded generation, are an essential input for reliable and economic power system operation, and energy trading. While such forecast...
{"title":"Additive Covariance Matrix Models: Modelling Regional Electricity Net-Demand in Great Britain","authors":"Vincenzo Gioia, Matteo Fasiolo, Jethro Browell, Ruggero Bellio","doi":"10.1080/01621459.2024.2412361","DOIUrl":"https://doi.org/10.1080/01621459.2024.2412361","url":null,"abstract":"Forecasts of regional electricity net-demand, consumption minus embedded generation, are an essential input for reliable and economic power system operation, and energy trading. While such forecast...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"70 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142448729","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 : 2024-10-10DOI: 10.1080/01621459.2024.2413928
Carolina Luque, Juan Sosa
This manuscript extensively reviews applications, extensions, and models derived from the Bayesian ideal point estimator. We focus our attention on studies conducted in the United States as well as...
本手稿广泛评述了贝叶斯理想点估计器的应用、扩展和衍生模型。我们重点关注在美国进行的研究以及...
{"title":"Operationalizing Legislative Bodies: A Methodological and Empirical Perspective with a Bayesian Approach","authors":"Carolina Luque, Juan Sosa","doi":"10.1080/01621459.2024.2413928","DOIUrl":"https://doi.org/10.1080/01621459.2024.2413928","url":null,"abstract":"This manuscript extensively reviews applications, extensions, and models derived from the Bayesian ideal point estimator. We focus our attention on studies conducted in the United States as well as...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"58 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142486732","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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