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Grid Point Approximation for Distributed Nonparametric Smoothing and Prediction 用于分布式非参数平滑和预测的网格点近似法
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-03 DOI: 10.1080/10618600.2024.2409817
Yuan Gao, Rui Pan, Feng Li, Riquan Zhang, Hansheng Wang
{"title":"Grid Point Approximation for Distributed Nonparametric Smoothing and Prediction","authors":"Yuan Gao, Rui Pan, Feng Li, Riquan Zhang, Hansheng Wang","doi":"10.1080/10618600.2024.2409817","DOIUrl":"https://doi.org/10.1080/10618600.2024.2409817","url":null,"abstract":"Kernel smoothing is a widely used nonparametric method in modern statistical analysis. The problem of efficiently conducting kernel smoothing for a massive dataset on a distributed system is a prob...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"11 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439969","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
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
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":"103 1","pages":""},"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":"1 1","pages":""},"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":"398 1","pages":""},"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
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