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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
Efficient Modeling of Spatial Extremes over Large Geographical Domains 大地理区域空间极值的高效建模
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-08 DOI: 10.1080/10618600.2024.2409784
Arnab Hazra, Raphaël Huser, David Bolin
{"title":"Efficient Modeling of Spatial Extremes over Large Geographical Domains","authors":"Arnab Hazra, Raphaël Huser, David Bolin","doi":"10.1080/10618600.2024.2409784","DOIUrl":"https://doi.org/10.1080/10618600.2024.2409784","url":null,"abstract":"Various natural phenomena exhibit spatial extremal dependence at short spatial distances. However, existing models proposed in the spatial extremes literature often assume that extremal dependence ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"70 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397716","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
Differentially Private Inference for Compositional Data 组合数据的差异化私有推理
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-07 DOI: 10.1080/10618600.2024.2412174
Qi Guo, Andrés F. Barrientos, Víctor Peña
{"title":"Differentially Private Inference for Compositional Data","authors":"Qi Guo, Andrés F. Barrientos, Víctor Peña","doi":"10.1080/10618600.2024.2412174","DOIUrl":"https://doi.org/10.1080/10618600.2024.2412174","url":null,"abstract":"Confidential data, such as electronic health records, activity data from wearable devices, and geolocation data, are becoming increasingly prevalent. Differential privacy provides a framework to co...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"18 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444355","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
MCMC for Bayesian nonparametric mixture modeling under differential privacy 差异隐私下贝叶斯非参数混合建模的 MCMC
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-07 DOI: 10.1080/10618600.2024.2410911
Mario Beraha, Stefano Favaro, Vinayak Rao
{"title":"MCMC for Bayesian nonparametric mixture modeling under differential privacy","authors":"Mario Beraha, Stefano Favaro, Vinayak Rao","doi":"10.1080/10618600.2024.2410911","DOIUrl":"https://doi.org/10.1080/10618600.2024.2410911","url":null,"abstract":"Estimating the probability density of a population while preserving the privacy of individuals in that population is an important and challenging problem that has received considerable attention in...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"103 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439968","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
Network embedding-based directed community detection with unknown community number 基于网络嵌入的定向群落检测与未知群落编号
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-10-04 DOI: 10.1080/10618600.2024.2409789
Qingzhao Zhang, Jinlong Zhou, Mingyang Ren
{"title":"Network embedding-based directed community detection with unknown community number","authors":"Qingzhao Zhang, Jinlong Zhou, Mingyang Ren","doi":"10.1080/10618600.2024.2409789","DOIUrl":"https://doi.org/10.1080/10618600.2024.2409789","url":null,"abstract":"Community detection of network analysis plays an important role in numerous application areas, in which estimating the number of communities is a fundamental issue. However, many existing methods f...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"13 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142486662","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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