Pub Date : 2024-09-26DOI: 10.1080/01621459.2024.2406583
Bikram Karmakar, Gourab Mukherjee, Wreetabrata Kar
Amid increasing awareness regarding opioid addiction, medical marijuana has emerged as a substitute to opioids for pain management. Concurrently, opioid manufacturers are putting significant resear...
{"title":"Using Penalized Synthetic Controls on Truncated data: A Case Study on Effect of Marijuana Legalization on Direct Payments to Physicians by Opioid Manufacturers","authors":"Bikram Karmakar, Gourab Mukherjee, Wreetabrata Kar","doi":"10.1080/01621459.2024.2406583","DOIUrl":"https://doi.org/10.1080/01621459.2024.2406583","url":null,"abstract":"Amid increasing awareness regarding opioid addiction, medical marijuana has emerged as a substitute to opioids for pain management. Concurrently, opioid manufacturers are putting significant resear...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"08 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142325562","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 : 2024-09-23DOI: 10.1080/01621459.2024.2404265
Joshua Agterberg, Anru R. Zhang
Higher-order multiway data is ubiquitous in machine learning and statistics and often exhibits community-like structures, where each component (node) along each different mode has a community membe...
{"title":"Estimating Higher-Order Mixed Memberships via the ℓ2,∞ Tensor Perturbation Bound","authors":"Joshua Agterberg, Anru R. Zhang","doi":"10.1080/01621459.2024.2404265","DOIUrl":"https://doi.org/10.1080/01621459.2024.2404265","url":null,"abstract":"Higher-order multiway data is ubiquitous in machine learning and statistics and often exhibits community-like structures, where each component (node) along each different mode has a community membe...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"21 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142317731","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 : 2024-09-20DOI: 10.1080/01621459.2024.2402565
Jiaxin Qiu, Zeng Li, Jianfeng Yao
Determining the number of factors in high-dimensional factor modeling is essential but challenging, especially when the data are heavy-tailed. In this paper, we introduce a new estimator based on t...
{"title":"Robust estimation for number of factors in high dimensional factor modeling via Spearman correlation matrix","authors":"Jiaxin Qiu, Zeng Li, Jianfeng Yao","doi":"10.1080/01621459.2024.2402565","DOIUrl":"https://doi.org/10.1080/01621459.2024.2402565","url":null,"abstract":"Determining the number of factors in high-dimensional factor modeling is essential but challenging, especially when the data are heavy-tailed. In this paper, we introduce a new estimator based on t...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"21 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142276071","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 : 2024-09-20DOI: 10.1080/01621459.2024.2402567
Ye Tian, Yang Feng
Most existing classification methods aim to minimize the overall misclassification error rate. However, in applications such as loan default prediction, different types of errors can have varying c...
{"title":"Neyman-Pearson Multi-class Classification via Cost-sensitive Learning","authors":"Ye Tian, Yang Feng","doi":"10.1080/01621459.2024.2402567","DOIUrl":"https://doi.org/10.1080/01621459.2024.2402567","url":null,"abstract":"Most existing classification methods aim to minimize the overall misclassification error rate. However, in applications such as loan default prediction, different types of errors can have varying c...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"106 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142317732","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 : 2024-09-20DOI: 10.1080/01621459.2024.2403788
Caihong Qin, Jinhan Xie, Ting Li, Yang Bai
In this paper, we study the transfer learning problem in functional classification, aiming to improve the classification accuracy of the target data by leveraging information from related source da...
本文研究了功能分类中的迁移学习问题，旨在通过利用相关源数据的信息来提高目标数据的分类精度。
{"title":"An Adaptive Transfer Learning Framework for Functional Classification","authors":"Caihong Qin, Jinhan Xie, Ting Li, Yang Bai","doi":"10.1080/01621459.2024.2403788","DOIUrl":"https://doi.org/10.1080/01621459.2024.2403788","url":null,"abstract":"In this paper, we study the transfer learning problem in functional classification, aiming to improve the classification accuracy of the target data by leveraging information from related source da...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"3 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142374037","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}
Graph Neural Networks (GNNs) have achieved promising performance in a variety of graph-focused tasks. Despite their success, however, existing GNNs suffer from two significant limitations: a lack o...
{"title":"A Model-Agnostic Graph Neural Network for Integrating Local and Global Information","authors":"Wenzhuo Zhou, Annie Qu, Keiland W. Cooper, Norbert Fortin, Babak Shahbaba","doi":"10.1080/01621459.2024.2404668","DOIUrl":"https://doi.org/10.1080/01621459.2024.2404668","url":null,"abstract":"Graph Neural Networks (GNNs) have achieved promising performance in a variety of graph-focused tasks. Despite their success, however, existing GNNs suffer from two significant limitations: a lack o...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"6 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142384072","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 : 2024-09-20DOI: 10.1080/01621459.2024.2403188
Yan Song, Wenlin Dai, Marc G. Genton
Low-rank approximation is a popular strategy to tackle the “big n problem” associated with large-scale Gaussian process regressions. Basis functions for developing low-rank structures are crucial a...
低阶近似是解决与大规模高斯过程回归相关的 "大 n 问题 "的一种流行策略。开发低秩结构的基础函数对解决大规模高斯过程回归的 "大 n 问题 "至关重要。
{"title":"Large-Scale Low-Rank Gaussian Process Prediction with Support Points","authors":"Yan Song, Wenlin Dai, Marc G. Genton","doi":"10.1080/01621459.2024.2403188","DOIUrl":"https://doi.org/10.1080/01621459.2024.2403188","url":null,"abstract":"Low-rank approximation is a popular strategy to tackle the “big n problem” associated with large-scale Gaussian process regressions. Basis functions for developing low-rank structures are crucial a...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"119 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142276069","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 : 2024-09-20DOI: 10.1080/01621459.2024.2404259
Ping Ma, Yongkai Chen, Haoran Lu, Wenxuan Zhong
With the rapid development of quantum computers, researchers have shown quantum advantages in physics-oriented problems. Quantum algorithms tackling computational biology problems are still lacking...
{"title":"Bisection Grover’s Search Algorithm and Its Application in Analyzing CITE-seq Data","authors":"Ping Ma, Yongkai Chen, Haoran Lu, Wenxuan Zhong","doi":"10.1080/01621459.2024.2404259","DOIUrl":"https://doi.org/10.1080/01621459.2024.2404259","url":null,"abstract":"With the rapid development of quantum computers, researchers have shown quantum advantages in physics-oriented problems. Quantum algorithms tackling computational biology problems are still lacking...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"77 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142276068","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}
A model-based approach is developed for clustering categorical data with no natural ordering. The proposed method exploits the Hamming distance to define a family of probability mass functions to m...
{"title":"Model-based clustering of categorical data based on the Hamming distance","authors":"Raffaele Argiento, Edoardo Filippi-Mazzola, Lucia Paci","doi":"10.1080/01621459.2024.2402568","DOIUrl":"https://doi.org/10.1080/01621459.2024.2402568","url":null,"abstract":"A model-based approach is developed for clustering categorical data with no natural ordering. The proposed method exploits the Hamming distance to define a family of probability mass functions to m...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"38 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142325564","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 : 2024-09-20DOI: 10.1080/01621459.2024.2402566
Jingfu Peng, Yang Li, Yuhong Yang
In the past decades, model averaging (MA) has attracted much attention as it has emerged as an alternative tool to the model selection (MS) statistical approach. Hansen (2007) introduced a Mallows ...
{"title":"On Optimality of Mallows Model Averaging*†","authors":"Jingfu Peng, Yang Li, Yuhong Yang","doi":"10.1080/01621459.2024.2402566","DOIUrl":"https://doi.org/10.1080/01621459.2024.2402566","url":null,"abstract":"In the past decades, model averaging (MA) has attracted much attention as it has emerged as an alternative tool to the model selection (MS) statistical approach. Hansen (2007) introduced a Mallows ...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"22 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142325359","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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