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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":null,"pages":null},"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
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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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
Bootstrap inference for linear time-varying coefficient models in locally stationary time series 局部静止时间序列中线性时变系数模型的引导推断
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-19 DOI: 10.1080/10618600.2024.2403705
Yicong Lin, Mingxuan Song, Bernhard van der Sluis
{"title":"Bootstrap inference for linear time-varying coefficient models in locally stationary time series","authors":"Yicong Lin, Mingxuan Song, Bernhard van der Sluis","doi":"10.1080/10618600.2024.2403705","DOIUrl":"https://doi.org/10.1080/10618600.2024.2403705","url":null,"abstract":"Time-varying coefficient models can capture evolving relationships. However, constructing asymptotic confidence bands for coefficient curves in these models is challenging due to slow convergence r...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321117","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
Approximate cross-validated mean estimates for Bayesian hierarchical regression models 贝叶斯分层回归模型的近似交叉验证平均估计值
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-18 DOI: 10.1080/10618600.2024.2404711
Amy Zhang, Michael J. Daniels, Changcheng Li, Le Bao
{"title":"Approximate cross-validated mean estimates for Bayesian hierarchical regression models","authors":"Amy Zhang, Michael J. Daniels, Changcheng Li, Le Bao","doi":"10.1080/10618600.2024.2404711","DOIUrl":"https://doi.org/10.1080/10618600.2024.2404711","url":null,"abstract":"We introduce a novel procedure for obtaining cross-validated predictive estimates for Bayesian hierarchical regression models (BHRMs). BHRMs are popular for modeling complex dependence structures (...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321118","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
Wasserstein-Kaplan-Meier Survival Regression Wasserstein-Kaplan-Meier 生存回归
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-17 DOI: 10.1080/10618600.2024.2404708
Yidong Zhou, Hans-Georg Müller
{"title":"Wasserstein-Kaplan-Meier Survival Regression","authors":"Yidong Zhou, Hans-Georg Müller","doi":"10.1080/10618600.2024.2404708","DOIUrl":"https://doi.org/10.1080/10618600.2024.2404708","url":null,"abstract":"Survival analysis plays a pivotal role in medical research, offering valuable insights into the timing of events such as survival time. One common challenge in survival analysis is the necessity to...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245215","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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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
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