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Functional Time Series Analysis and Visualization Based on Records 基于记录的功能时间序列分析和可视化
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10618600.2024.2374578
Israel Martínez-Hernández, Marc G. Genton
{"title":"Functional Time Series Analysis and Visualization Based on Records","authors":"Israel Martínez-Hernández, Marc G. Genton","doi":"10.1080/10618600.2024.2374578","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374578","url":null,"abstract":"In many phenomena, data are collected on a large scale and at different frequencies. In this context, functional data analysis (FDA) has become an important statistical methodology for analyzing an...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"25 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141557125","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
Stochastic Block Smooth Graphon Model 随机块平滑图模型
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10618600.2024.2374571
Benjamin Sischka, Göran Kauermann
{"title":"Stochastic Block Smooth Graphon Model","authors":"Benjamin Sischka, Göran Kauermann","doi":"10.1080/10618600.2024.2374571","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374571","url":null,"abstract":"In this paper, we propose combining the stochastic blockmodel and the smooth graphon model, two of the most prominent modeling approaches in statistical network analysis. Stochastic blockmodels are...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"40 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597633","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
Continuous-time multivariate analysis 连续时间多元分析
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10618600.2024.2374570
Biplab Paul, Philip T. Reiss, Erjia Cui, Noemi Foà
{"title":"Continuous-time multivariate analysis","authors":"Biplab Paul, Philip T. Reiss, Erjia Cui, Noemi Foà","doi":"10.1080/10618600.2024.2374570","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374570","url":null,"abstract":"The starting point for much of multivariate analysis (MVA) is an n × p data matrix whose n rows represent observations and whose p columns represent variables. Some multivariate data sets, however,...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"20 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597579","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 Tidy Framework and Infrastructure to Systematically Assemble Spatio-temporal Indexes from Multivariate Data 从多变量数据中系统汇集时空索引的整洁框架和基础设施
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10618600.2024.2374960
H. Sherry Zhang, Dianne Cook, Ursula Laa, Nicolas Langrené, Patricia Menéndez
{"title":"A Tidy Framework and Infrastructure to Systematically Assemble Spatio-temporal Indexes from Multivariate Data","authors":"H. Sherry Zhang, Dianne Cook, Ursula Laa, Nicolas Langrené, Patricia Menéndez","doi":"10.1080/10618600.2024.2374960","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374960","url":null,"abstract":"Indexes are useful for summarizing multivariate information into single metrics for monitoring, communicating, and decision-making. While most work has focused on defining new indexes for specific ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"153 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597599","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
Dynamic prediction using landmark historical functional Cox regression 利用地标历史功能 Cox 回归进行动态预测
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-02 DOI: 10.1080/10618600.2024.2374576
Andrew Leroux, Ciprian Crainiceanu
{"title":"Dynamic prediction using landmark historical functional Cox regression","authors":"Andrew Leroux, Ciprian Crainiceanu","doi":"10.1080/10618600.2024.2374576","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374576","url":null,"abstract":"Dynamic prediction of survival data in the presence of time-varying covariates is an area of active research. Two common analytic approaches for this type of data are joint modeling of the longitud...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"34 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584477","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
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
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
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