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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
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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
Distortion corrected kernel density estimator on Riemannian manifolds 黎曼流形上的失真校正核密度估算器
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-24 DOI: 10.1080/10618600.2024.2415543
Fan Cheng, Rob J Hyndman, Anastasios Panagiotelis
{"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}
引用次数: 0
Qini Curves for Multi-Armed Treatment Rules 多臂处理规则的基尼曲线
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-24 DOI: 10.1080/10618600.2024.2418820
Erik Sverdrup, Han Wu, Susan Athey, Stefan Wager
{"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}
引用次数: 0
Efficient Sampling From the Watson Distribution in Arbitrary Dimensions 从任意维度的沃森分布中高效取样
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-23 DOI: 10.1080/10618600.2024.2416521
Lukas Sablica, Kurt Hornik, Josef Leydold
{"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}
引用次数: 0
AddiVortes: (Bayesian) Additive Voronoi Tessellations AddiVortes：（贝叶斯）加法沃罗诺网状结构
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-16 DOI: 10.1080/10618600.2024.2414104
Adam. J. Stone, John Paul Gosling
{"title":"AddiVortes: (Bayesian) Additive Voronoi Tessellations","authors":"Adam. J. Stone, John Paul Gosling","doi":"10.1080/10618600.2024.2414104","DOIUrl":"https://doi.org/10.1080/10618600.2024.2414104","url":null,"abstract":"The Additive Voronoi Tessellations (AddiVortes) model is a multivariate regression model that uses Voronoi tessellations to partition the covariate space in an additive ensemble model. Unlike other...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"92 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439805","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
Sample efficient nonparametric regression via low-rank regularization 通过低秩正则化实现样本高效非参数回归
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-15 DOI: 10.1080/10618600.2024.2414891
Jiakun Jiang, Jiahao Peng, Heng Lian
{"title":"Sample efficient nonparametric regression via low-rank regularization","authors":"Jiakun Jiang, Jiahao Peng, Heng Lian","doi":"10.1080/10618600.2024.2414891","DOIUrl":"https://doi.org/10.1080/10618600.2024.2414891","url":null,"abstract":"Nonparametric regression suffers from curse of dimensionality, requiring a relatively large sample size for accurate estimation beyond the univariate case. In this paper, we consider a simple metho...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"23 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439935","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
Scalable Clustering: Large Scale Unsupervised Learning of Gaussian Mixture Models with Outliers 可扩展聚类：有异常值的高斯混杂模型的大规模无监督学习
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-14 DOI: 10.1080/10618600.2024.2414889
Yijia Zhou, Kyle A. Gallivan, Adrian Barbu
{"title":"Scalable Clustering: Large Scale Unsupervised Learning of Gaussian Mixture Models with Outliers","authors":"Yijia Zhou, Kyle A. Gallivan, Adrian Barbu","doi":"10.1080/10618600.2024.2414889","DOIUrl":"https://doi.org/10.1080/10618600.2024.2414889","url":null,"abstract":"Clustering is a widely used technique with a long and rich history in a variety of areas. However, most existing algorithms do not scale well to large datasets, or are missing theoretical guarantee...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"32 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439807","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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