Pub Date : 2024-11-05DOI: 10.1080/10618600.2024.2422985
Jan O. Bauer
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...
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Pub Date : 2024-10-31DOI: 10.1080/10618600.2024.2421246
Jingfei Zhang, Yi Li
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...
{"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}
Pub Date : 2024-10-31DOI: 10.1080/10618600.2024.2421990
Jun Yu, Zhiqiang Ye, Mingyao Ai, Ping Ma
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...
{"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}
Pub Date : 2024-10-31DOI: 10.1080/10618600.2024.2421984
Rosario Barone, Alessio Farcomeni, Maura Mezzetti
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....
{"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}
Pub Date : 2024-10-28DOI: 10.1080/10618600.2024.2414113
Yeqing Zhou, Fei Jiang
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...
{"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}
Pub Date : 2024-10-28DOI: 10.1080/10618600.2024.2421248
Fan Bi, Jianan Zhu, Yang Feng
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...
{"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}
Pub Date : 2024-10-24DOI: 10.1080/10618600.2024.2418817
Upasana Dutta, Bailey K. Fosdick, Aaron Clauset
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...
{"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}
Pub Date : 2024-10-24DOI: 10.1080/10618600.2024.2415543
Fan Cheng, Rob J Hyndman, Anastasios Panagiotelis
Manifold learning obtains a low-dimensional representation of an underlying Riemannian manifold supporting high-dimensional data. Kernel density estimates of the low-dimensional embedding with a fi...
{"title":"Distortion corrected kernel density estimator on Riemannian manifolds","authors":"Fan Cheng, Rob J Hyndman, Anastasios Panagiotelis","doi":"10.1080/10618600.2024.2415543","DOIUrl":"https://doi.org/10.1080/10618600.2024.2415543","url":null,"abstract":"Manifold learning obtains a low-dimensional representation of an underlying Riemannian manifold supporting high-dimensional data. Kernel density estimates of the low-dimensional embedding with a fi...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"212 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142490778","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}
Pub Date : 2024-10-24DOI: 10.1080/10618600.2024.2418820
Erik Sverdrup, Han Wu, Susan Athey, Stefan Wager
Qini curves have emerged as an attractive and popular approach for evaluating the benefit of data-driven targeting rules for treatment allocation. We propose a generalization of the Qini curve to m...
{"title":"Qini Curves for Multi-Armed Treatment Rules","authors":"Erik Sverdrup, Han Wu, Susan Athey, Stefan Wager","doi":"10.1080/10618600.2024.2418820","DOIUrl":"https://doi.org/10.1080/10618600.2024.2418820","url":null,"abstract":"Qini curves have emerged as an attractive and popular approach for evaluating the benefit of data-driven targeting rules for treatment allocation. We propose a generalization of the Qini curve to m...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"10 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142490777","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}
Pub Date : 2024-10-23DOI: 10.1080/10618600.2024.2416521
Lukas Sablica, Kurt Hornik, Josef Leydold
In this paper, we present two efficient methods for sampling from the Watson distribution in arbitrary dimensions. The first method adapts the rejection sampling algorithm from Kent et al. (2018), ...
本文提出了两种从任意维度的沃森分布中采样的高效方法。第一种方法采用了 Kent 等人（2018）的拒绝采样算法， ...
{"title":"Efficient Sampling From the Watson Distribution in Arbitrary Dimensions","authors":"Lukas Sablica, Kurt Hornik, Josef Leydold","doi":"10.1080/10618600.2024.2416521","DOIUrl":"https://doi.org/10.1080/10618600.2024.2416521","url":null,"abstract":"In this paper, we present two efficient methods for sampling from the Watson distribution in arbitrary dimensions. The first method adapts the rejection sampling algorithm from Kent et al. (2018), ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"105 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142489709","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}
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