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Bootstrapped Edge Count Tests for Nonparametric Two-Sample Inference Under Heterogeneity 异质性条件下用于非参数双样本推断的引导边缘计数检验
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-01 DOI: 10.1080/10618600.2024.2374583
Trambak Banerjee, Bhaswar B. Bhattacharya, Gourab Mukherjee
{"title":"Bootstrapped Edge Count Tests for Nonparametric Two-Sample Inference Under Heterogeneity","authors":"Trambak Banerjee, Bhaswar B. Bhattacharya, Gourab Mukherjee","doi":"10.1080/10618600.2024.2374583","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374583","url":null,"abstract":"Nonparametric two-sample testing is a classical problem in inferential statistics. While modern two-sample tests, such as the edge count test and its variants, can handle multivariate and non-Eucli...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"31 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489583","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
On the Wasserstein Median of Probability Measures 论概率度量的瓦瑟斯坦中值
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-01 DOI: 10.1080/10618600.2024.2374580
Kisung You, Dennis Shung, Mauro Giuffrè
{"title":"On the Wasserstein Median of Probability Measures","authors":"Kisung You, Dennis Shung, Mauro Giuffrè","doi":"10.1080/10618600.2024.2374580","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374580","url":null,"abstract":"The primary choice to summarize a finite collection of random objects is by using measures of central tendency, such as mean and median. In the field of optimal transport, the Wasserstein barycente...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"55 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584475","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
Global inference and test for eigensystems of imaging data over complicated domains 复杂域上成像数据特征系统的全局推理和测试
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-01 DOI: 10.1080/10618600.2024.2374584
Leheng Cai, Qirui Hu
{"title":"Global inference and test for eigensystems of imaging data over complicated domains","authors":"Leheng Cai, Qirui Hu","doi":"10.1080/10618600.2024.2374584","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374584","url":null,"abstract":"A nonparametric approach for analyzing eigensystems of image data over a complex domain is novelly developed. The proposed estimators, which are based on bivariate splines, have both oracle efficie...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"93 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489569","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
Bayesian L12 regression 贝叶斯 L12 回归
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-01 DOI: 10.1080/10618600.2024.2374579
Xiongwen Ke, Yanan Fan
{"title":"Bayesian L12 regression","authors":"Xiongwen Ke, Yanan Fan","doi":"10.1080/10618600.2024.2374579","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374579","url":null,"abstract":"It is well known that Bridge regression Knight et al. (2000) enjoys superior theoretical properties when compared to traditional LASSO. However, the current latent variable representation of its Ba...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"13 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141557126","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
Principal variables analysis for non-Gaussian data 非高斯数据的主变量分析
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-06-13 DOI: 10.1080/10618600.2024.2367098
Dylan Clark-Boucher, Jeffrey W. Miller
{"title":"Principal variables analysis for non-Gaussian data","authors":"Dylan Clark-Boucher, Jeffrey W. Miller","doi":"10.1080/10618600.2024.2367098","DOIUrl":"https://doi.org/10.1080/10618600.2024.2367098","url":null,"abstract":"Principal variables analysis (PVA) is a technique for selecting a subset of variables that capture as much of the information in a dataset as possible. Existing approaches for PVA are based on the ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"33 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315750","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 distribution-free method for change point detection in non-sparse high dimensional data 在非稀疏高维数据中检测变化点的无分布方法
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-06-12 DOI: 10.1080/10618600.2024.2365733
Reza Drikvandi, Reza Modarres
{"title":"A distribution-free method for change point detection in non-sparse high dimensional data","authors":"Reza Drikvandi, Reza Modarres","doi":"10.1080/10618600.2024.2365733","DOIUrl":"https://doi.org/10.1080/10618600.2024.2365733","url":null,"abstract":"We propose a distribution-free distance-based method for high dimensional change points that can address challenging situations when the sample size is very small compared to the dimension as in th...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"21 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141333665","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
Generating Independent Replicates Directly from the Posterior Distribution for a Class of Spatial Hierarchical Models 直接从一类空间层次模型的后验分布生成独立副本
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-06-11 DOI: 10.1080/10618600.2024.2365728
Jonathan R. Bradley, Madelyn Clinch
{"title":"Generating Independent Replicates Directly from the Posterior Distribution for a Class of Spatial Hierarchical Models","authors":"Jonathan R. Bradley, Madelyn Clinch","doi":"10.1080/10618600.2024.2365728","DOIUrl":"https://doi.org/10.1080/10618600.2024.2365728","url":null,"abstract":"Markov chain Monte Carlo (MCMC) allows one to generate dependent replicates from a posterior distribution for effectively any Bayesian hierarchical model. However, MCMC can produce a significant co...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"6 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141309042","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
Testing Model Specification in Approximate Bayesian Computation Using Asymptotic Properties 利用渐近特性检验近似贝叶斯计算中的模型规范
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-06-11 DOI: 10.1080/10618600.2024.2357630
Andrés Ramírez-Hassan, David T. Frazier
{"title":"Testing Model Specification in Approximate Bayesian Computation Using Asymptotic Properties","authors":"Andrés Ramírez-Hassan, David T. Frazier","doi":"10.1080/10618600.2024.2357630","DOIUrl":"https://doi.org/10.1080/10618600.2024.2357630","url":null,"abstract":"We present a novel procedure to diagnose model misspecification in situations where inference is performed using approximate Bayesian computation (ABC). Unlike previous procedures, our proposal is ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"39 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141308943","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
Interval-censored linear quantile regression 区间截断线性量回归
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-06-11 DOI: 10.1080/10618600.2024.2365740
Taehwa Choi, Seohyeon Park, Hunyong Cho, Sangbum Choi
{"title":"Interval-censored linear quantile regression","authors":"Taehwa Choi, Seohyeon Park, Hunyong Cho, Sangbum Choi","doi":"10.1080/10618600.2024.2365740","DOIUrl":"https://doi.org/10.1080/10618600.2024.2365740","url":null,"abstract":"Censored quantile regression has emerged as a prominent alternative to classical Cox’s proportional hazards model or accelerated failure time model in both theoretical and applied statistics. While...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"2 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141309146","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
Distance-based clustering of functional data with derivative principal component analysis 利用衍生主成分分析对功能数据进行基于距离的聚类
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-06-11 DOI: 10.1080/10618600.2024.2366499
Ping Yu, Gongmin Shi, Chunjie Wang, Xinyuan Song
{"title":"Distance-based clustering of functional data with derivative principal component analysis","authors":"Ping Yu, Gongmin Shi, Chunjie Wang, Xinyuan Song","doi":"10.1080/10618600.2024.2366499","DOIUrl":"https://doi.org/10.1080/10618600.2024.2366499","url":null,"abstract":"Functional data analysis (FDA) is an important modern paradigm for handling infinite-dimensional data. An important task in FDA is clustering, which identifies subgroups based on the shapes of meas...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"16 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141333663","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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