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Journal of Computational and Graphical Statistics最新文献

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FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions FAStEN：高维函数回归中特征选择和估计的高效自适应方法
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-27 DOI: 10.1080/10618600.2024.2407464
Tobia Boschi, Lorenzo Testa, Francesca Chiaromonte, Matthew Reimherr
{"title":"FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions","authors":"Tobia Boschi, Lorenzo Testa, Francesca Chiaromonte, Matthew Reimherr","doi":"10.1080/10618600.2024.2407464","DOIUrl":"https://doi.org/10.1080/10618600.2024.2407464","url":null,"abstract":"Functional regression analysis is an established tool for many contemporary scientific applications. Regression problems involving large and complex data sets are ubiquitous, and feature selection ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"37 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Multivariate moment least-squares variance estimators for reversible Markov chains 可逆马尔可夫链的多元矩最小二乘方差估计器
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-27 DOI: 10.1080/10618600.2024.2407458
Hyebin Song, Stephen Berg
{"title":"Multivariate moment least-squares variance estimators for reversible Markov chains","authors":"Hyebin Song, Stephen Berg","doi":"10.1080/10618600.2024.2407458","DOIUrl":"https://doi.org/10.1080/10618600.2024.2407458","url":null,"abstract":"Markov chain Monte Carlo (MCMC) is a commonly used method for approximating expectations with respect to probability distributions. Uncertainty assessment for MCMC estimators is essential in practi...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"10 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142374092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Covariance Assisted Multivariate Penalized Additive Regression (CoMPAdRe) 协方差辅助多元惩罚加性回归（CoMPAdRe）
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-27 DOI: 10.1080/10618600.2024.2407453
Neel Desai, Veerabhadran Baladandayuthapani, Russell T. Shinohara, Jeffrey S. Morris
{"title":"Covariance Assisted Multivariate Penalized Additive Regression (CoMPAdRe)","authors":"Neel Desai, Veerabhadran Baladandayuthapani, Russell T. Shinohara, Jeffrey S. Morris","doi":"10.1080/10618600.2024.2407453","DOIUrl":"https://doi.org/10.1080/10618600.2024.2407453","url":null,"abstract":"We propose a new method for the simultaneous selection and estimation of multivariate sparse additive models with correlated errors. Our method called Covariance Assisted Multivariate Penalized Add...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"66 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
A Latent Space Model for Weighted Keyword Co-occurrence Networks with Applications in Knowledge Discovery in Statistics 加权关键词共现网络的潜空间模型及其在统计知识发现中的应用
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-27 DOI: 10.1080/10618600.2024.2407465
Yan Zhang, Rui Pan, Xuening Zhu, Kuangnan Fang, Hansheng Wang
{"title":"A Latent Space Model for Weighted Keyword Co-occurrence Networks with Applications in Knowledge Discovery in Statistics","authors":"Yan Zhang, Rui Pan, Xuening Zhu, Kuangnan Fang, Hansheng Wang","doi":"10.1080/10618600.2024.2407465","DOIUrl":"https://doi.org/10.1080/10618600.2024.2407465","url":null,"abstract":"Keywords are widely recognized as pivotal in conveying the central idea of academic articles. In this article, we construct a weighted and dynamic keyword co-occurrence network and propose a latent...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"120 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
TSLiNGAM: DirectLiNGAM Under Heavy Tails TSLiNGAM：沉重尾巴下的 DirectLiNGAM
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-27 DOI: 10.1080/10618600.2024.2394462
Sarah Leyder, Jakob Raymaekers, Tim Verdonck
{"title":"TSLiNGAM: DirectLiNGAM Under Heavy Tails","authors":"Sarah Leyder, Jakob Raymaekers, Tim Verdonck","doi":"10.1080/10618600.2024.2394462","DOIUrl":"https://doi.org/10.1080/10618600.2024.2394462","url":null,"abstract":"One of the established approaches to causal discovery consists of combining directed acyclic graphs (DAGs) with structural causal models (SCMs) to describe the functional dependencies of effects on...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"23 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142374091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Efficient Nonparametric Estimation of 3D Point Cloud Signals through Distributed Learning 通过分布式学习实现三维点云信号的高效非参数估计
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-24 DOI: 10.1080/10618600.2024.2406301
Guannan Wang, Yuchun Wang, Annie S. Gao, Li Wang
{"title":"Efficient Nonparametric Estimation of 3D Point Cloud Signals through Distributed Learning","authors":"Guannan Wang, Yuchun Wang, Annie S. Gao, Li Wang","doi":"10.1080/10618600.2024.2406301","DOIUrl":"https://doi.org/10.1080/10618600.2024.2406301","url":null,"abstract":"Advancements in technology have elevated the prominence of 3D point cloud data, making its analysis increasingly vital across various applications. This need drives the demand for advanced statisti...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"1 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Simultaneous coefficient clustering and sparsity for multivariate mixed models 多变量混合模型的同步系数聚类和稀疏性
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-13 DOI: 10.1080/10618600.2024.2402904
Francis K.C. Hui, Khue-Dung Dang, Luca Maestrini
{"title":"Simultaneous coefficient clustering and sparsity for multivariate mixed models","authors":"Francis K.C. Hui, Khue-Dung Dang, Luca Maestrini","doi":"10.1080/10618600.2024.2402904","DOIUrl":"https://doi.org/10.1080/10618600.2024.2402904","url":null,"abstract":"In many applications of multivariate longitudinal mixed models, it is reasonable to assume that each response is informed by only a subset of covariates. Moreover, one or more responses may exhibit...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"4 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142325074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Optimal Subsampling for Functional Quasi-Mode Regression with Big Data 大数据功能准模式回归的最佳子采样
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-12 DOI: 10.1080/10618600.2024.2402279
Tao Wang
{"title":"Optimal Subsampling for Functional Quasi-Mode Regression with Big Data","authors":"Tao Wang","doi":"10.1080/10618600.2024.2402279","DOIUrl":"https://doi.org/10.1080/10618600.2024.2402279","url":null,"abstract":"We propose investigating optimal subsampling for functional regression with massive datasets based on the mode value, which is referred to as functional quasi-mode regression, to reduce data volume...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"11 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Efficient Large-scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks 利用卷积神经网络进行高效的大规模非稳态空间协方差函数估计
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-12 DOI: 10.1080/10618600.2024.2402277
Pratik Nag, Yiping Hong, Sameh Abdulah, Ghulam A. Qadir, Marc G. Genton, Ying Sun
{"title":"Efficient Large-scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks","authors":"Pratik Nag, Yiping Hong, Sameh Abdulah, Ghulam A. Qadir, Marc G. Genton, Ying Sun","doi":"10.1080/10618600.2024.2402277","DOIUrl":"https://doi.org/10.1080/10618600.2024.2402277","url":null,"abstract":"Spatial processes observed in various fields, such as climate and environmental science, often occur at large-scale and demonstrate spatial nonstationarity. However, fitting a Gaussian process with...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"17 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Bayesian nowcasting with Laplacian-P-splines 利用拉普拉斯-P-样条曲线进行贝叶斯现时预测
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-12 DOI: 10.1080/10618600.2024.2395414
Bryan Sumalinab, Oswaldo Gressani, Niel Hens, Christel Faes
{"title":"Bayesian nowcasting with Laplacian-P-splines","authors":"Bryan Sumalinab, Oswaldo Gressani, Niel Hens, Christel Faes","doi":"10.1080/10618600.2024.2395414","DOIUrl":"https://doi.org/10.1080/10618600.2024.2395414","url":null,"abstract":"During an epidemic, the daily number of reported infected cases, deaths or hospitalizations is often lower than the actual number due to reporting delays. Nowcasting aims to estimate the cases that...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"29 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
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