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ProSpar-GP: Scalable Gaussian Process Modeling with Massive Nonstationary Datasets 大规模非平稳数据集的可伸缩高斯过程建模
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2025-04-09 DOI: 10.1080/10618600.2025.2490264
Kevin Li, Simon Mak
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引用次数: 0
Dependence-based fuzzy clustering of functional time series 基于依赖的函数时间序列模糊聚类
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2025-04-09 DOI: 10.1080/10618600.2025.2489537
Ángel López-Oriona, Ying Sun, Han Lin Shang
{"title":"Dependence-based fuzzy clustering of functional time series","authors":"Ángel López-Oriona, Ying Sun, Han Lin Shang","doi":"10.1080/10618600.2025.2489537","DOIUrl":"https://doi.org/10.1080/10618600.2025.2489537","url":null,"abstract":"","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"137 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144193807","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
Clustering Time-Evolving Networks Using Temporal Exponential-Family Random Graph Models with Conditional Dyadic Independence and Dynamic Latent Blocks 具有条件并矢独立性和动态潜在块的时间指数族随机图模型聚类时变网络
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2025-03-28 DOI: 10.1080/10618600.2025.2484011
Amal Agarwal, Kevin H. Lee, Lingzhou Xue
{"title":"Clustering Time-Evolving Networks Using Temporal Exponential-Family Random Graph Models with Conditional Dyadic Independence and Dynamic Latent Blocks","authors":"Amal Agarwal, Kevin H. Lee, Lingzhou Xue","doi":"10.1080/10618600.2025.2484011","DOIUrl":"https://doi.org/10.1080/10618600.2025.2484011","url":null,"abstract":"","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"142 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144193428","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
High-Dimensional Block Diagonal Covariance Structure Detection Using Singular Vectors 利用奇异矢量进行高维块对角线协方差结构检测
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-11-05 DOI: 10.1080/10618600.2024.2422985
Jan O. Bauer
{"title":"High-Dimensional Block Diagonal Covariance Structure Detection Using Singular Vectors","authors":"Jan O. Bauer","doi":"10.1080/10618600.2024.2422985","DOIUrl":"https://doi.org/10.1080/10618600.2024.2422985","url":null,"abstract":"The assumption of independent subvectors arises in many aspects of multivariate analysis. In most real-world applications, however, we lack prior knowledge about the number of subvectors and the sp...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"12 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142589065","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
Multi-task Learning for Gaussian Graphical Regressions with High Dimensional Covariates 高斯图形回归与高维变量的多任务学习
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-31 DOI: 10.1080/10618600.2024.2421246
Jingfei Zhang, Yi Li
{"title":"Multi-task Learning for Gaussian Graphical Regressions with High Dimensional Covariates","authors":"Jingfei Zhang, Yi Li","doi":"10.1080/10618600.2024.2421246","DOIUrl":"https://doi.org/10.1080/10618600.2024.2421246","url":null,"abstract":"Gaussian graphical regression is a powerful approach for regressing the precision matrix of a Gaussian graphical model on covariates, which permits the response variables and covariates to outnumbe...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"5 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142589068","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 Data Streams with Measurement Constrained Categorical Responses 测量受限分类响应数据流的最优子采样
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-31 DOI: 10.1080/10618600.2024.2421990
Jun Yu, Zhiqiang Ye, Mingyao Ai, Ping Ma
{"title":"Optimal Subsampling for Data Streams with Measurement Constrained Categorical Responses","authors":"Jun Yu, Zhiqiang Ye, Mingyao Ai, Ping Ma","doi":"10.1080/10618600.2024.2421990","DOIUrl":"https://doi.org/10.1080/10618600.2024.2421990","url":null,"abstract":"High-velocity, large-scale data streams have become pervasive. Frequently, the associated labels for such data prove costly to measure and are not always available upfront. Consequently, the analys...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"87 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142566130","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
Latent Markov time-interaction processes 潜在马尔可夫时间交互过程
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-31 DOI: 10.1080/10618600.2024.2421984
Rosario Barone, Alessio Farcomeni, Maura Mezzetti
{"title":"Latent Markov time-interaction processes","authors":"Rosario Barone, Alessio Farcomeni, Maura Mezzetti","doi":"10.1080/10618600.2024.2421984","DOIUrl":"https://doi.org/10.1080/10618600.2024.2421984","url":null,"abstract":"We present parametric and semiparametric latent Markov time-interaction processes, that are point processes where the occurrence of an event can increase or reduce the probability of future events....","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"35 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142589070","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
Heterogeneous functional regression for subgroup analysis 用于分组分析的异质功能回归
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-28 DOI: 10.1080/10618600.2024.2414113
Yeqing Zhou, Fei Jiang
{"title":"Heterogeneous functional regression for subgroup analysis","authors":"Yeqing Zhou, Fei Jiang","doi":"10.1080/10618600.2024.2414113","DOIUrl":"https://doi.org/10.1080/10618600.2024.2414113","url":null,"abstract":"With ever increasing number of features of modern datasets, data heterogeneity is gradually becoming the norm rather than the exception. Whereas classical regressions usually assume all the samples...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"61 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541820","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
Multi-label Random Subspace Ensemble Classification1 多标签随机子空间集合分类1
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-28 DOI: 10.1080/10618600.2024.2421248
Fan Bi, Jianan Zhu, Yang Feng
{"title":"Multi-label Random Subspace Ensemble Classification1","authors":"Fan Bi, Jianan Zhu, Yang Feng","doi":"10.1080/10618600.2024.2421248","DOIUrl":"https://doi.org/10.1080/10618600.2024.2421248","url":null,"abstract":"In this work, we develop a new ensemble learning framework, multi-label Random Subspace Ensemble (mRaSE), for multi-label classification. Given a base classifier (e.g., multinomial logistic regress...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"62 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541815","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
Sampling random graphs with specified degree sequences 对具有指定度序列的随机图形进行采样
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-24 DOI: 10.1080/10618600.2024.2418817
Upasana Dutta, Bailey K. Fosdick, Aaron Clauset
{"title":"Sampling random graphs with specified degree sequences","authors":"Upasana Dutta, Bailey K. Fosdick, Aaron Clauset","doi":"10.1080/10618600.2024.2418817","DOIUrl":"https://doi.org/10.1080/10618600.2024.2418817","url":null,"abstract":"The configuration model is a standard tool for uniformly generating random graphs with a specified degree sequence, and is often used as a null model to evaluate how much of an observed network’s s...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"27 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142566132","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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