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Journal of Nonparametric Statistics最新文献

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Errors-in-variables regression for mixed Euclidean and non-Euclidean predictors 欧氏和非欧氏混合预测变量的变量误差回归
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-07-24 DOI: 10.1080/10485252.2024.2378897
Jeong Min Jeon
{"title":"Errors-in-variables regression for mixed Euclidean and non-Euclidean predictors","authors":"Jeong Min Jeon","doi":"10.1080/10485252.2024.2378897","DOIUrl":"https://doi.org/10.1080/10485252.2024.2378897","url":null,"abstract":"In this paper, we explore a novel regression problem encompassing both Euclidean and non-Euclidean predictors, all of which are subject to measurement errors. Specifically, we focus on a non-Euclid...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"20 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141776266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Clustering of high-dimensional observations 高维观测数据的聚类
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-07-24 DOI: 10.1080/10485252.2024.2378904
Yong Wang, Reza Modarres
{"title":"Clustering of high-dimensional observations","authors":"Yong Wang, Reza Modarres","doi":"10.1080/10485252.2024.2378904","DOIUrl":"https://doi.org/10.1080/10485252.2024.2378904","url":null,"abstract":"We present a novel clustering method for high-dimensional, low sample size (HDLSS) data. The method is distance-based, takes advantage of the distance concentration phenomenon and the limiting valu...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"38 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141776149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Tracking full posterior in online Bayesian classification learning: a particle filter approach 在线贝叶斯分类学习中的全后验跟踪：粒子过滤器方法
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-07-09 DOI: 10.1080/10485252.2024.2368631
Enze Shi, Jinhan Xie, Shenggang Hu, Ke Sun, Hongsheng Dai, Bei Jiang, Linglong Kong, Lingzhu Li
{"title":"Tracking full posterior in online Bayesian classification learning: a particle filter approach","authors":"Enze Shi, Jinhan Xie, Shenggang Hu, Ke Sun, Hongsheng Dai, Bei Jiang, Linglong Kong, Lingzhu Li","doi":"10.1080/10485252.2024.2368631","DOIUrl":"https://doi.org/10.1080/10485252.2024.2368631","url":null,"abstract":"The rapid growth of data volume and velocity is challenging traditional methods of classification, making it impossible to store so much data in memory. Developing online classification methods is ...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"30 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141608361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Group inference of high-dimensional single-index models 高维单指数模型的分组推断
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-07-03 DOI: 10.1080/10485252.2024.2371524
Dongxiao Han, Miao Han, Meiling Hao, Liuquan Sun, Siyang Wang
{"title":"Group inference of high-dimensional single-index models","authors":"Dongxiao Han, Miao Han, Meiling Hao, Liuquan Sun, Siyang Wang","doi":"10.1080/10485252.2024.2371524","DOIUrl":"https://doi.org/10.1080/10485252.2024.2371524","url":null,"abstract":"For the supervised and semi-supervised settings, a group inference method is proposed for regression parameters in high-dimensional semi-parametric single-index models with an unknown random link f...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"78 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141608359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Nonparametric screening for additive quantile regression in ultra-high dimension 超高维度加法量化回归的非参数筛选
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-06-18 DOI: 10.1080/10485252.2024.2366978
Daoji Li, Yinfei Kong, Dawit Zerom
{"title":"Nonparametric screening for additive quantile regression in ultra-high dimension","authors":"Daoji Li, Yinfei Kong, Dawit Zerom","doi":"10.1080/10485252.2024.2366978","DOIUrl":"https://doi.org/10.1080/10485252.2024.2366978","url":null,"abstract":"In practical applications, one often does not know the ‘true’ structure of the underlying conditional quantile function, especially in the ultra-high dimensional setting. To deal with ultra-high di...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"31 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141529569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Trajectory clustering with adjustment for time-varying covariate effects 轨迹聚类，调整时变协变量效应
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-05-27 DOI: 10.1080/10485252.2024.2358435
Chunxi Liu, Chao Han, Weiping Zhang
{"title":"Trajectory clustering with adjustment for time-varying covariate effects","authors":"Chunxi Liu, Chao Han, Weiping Zhang","doi":"10.1080/10485252.2024.2358435","DOIUrl":"https://doi.org/10.1080/10485252.2024.2358435","url":null,"abstract":"In this paper, we propose a penalized regression method to detect subgroups of trajectories while accounting for the time-varying effects of given covariates. Specifically, we allow both the latent...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"67 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141507293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 novel framework for online supervised learning with feature selection 带特征选择的在线监督学习新框架
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-05-24 DOI: 10.1080/10485252.2024.2359057
Lizhe Sun, Mingyuan Wang, Siquan Zhu, Adrian Barbu
{"title":"A novel framework for online supervised learning with feature selection","authors":"Lizhe Sun, Mingyuan Wang, Siquan Zhu, Adrian Barbu","doi":"10.1080/10485252.2024.2359057","DOIUrl":"https://doi.org/10.1080/10485252.2024.2359057","url":null,"abstract":"Current online learning methods suffer issues such as lower convergence rates and limited capability to select important features compared to their offline counterparts. In this paper, a novel fram...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"40 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141529570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Equivalence between constrained optimal smoothing and Bayesian estimation 受限最优平滑法与贝叶斯估计法的等效性
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-05-03 DOI: 10.1080/10485252.2024.2348542
L. Grammont, H. Maatouk, X. Bay
{"title":"Equivalence between constrained optimal smoothing and Bayesian estimation","authors":"L. Grammont, H. Maatouk, X. Bay","doi":"10.1080/10485252.2024.2348542","DOIUrl":"https://doi.org/10.1080/10485252.2024.2348542","url":null,"abstract":"In this paper, we extend the correspondence between Bayesian estimation and optimal smoothing in a Reproducing Kernel Hilbert Space (RKHS) by adding convex constraints to the problem. Through a seq...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"35 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140929621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Data-driven resistant kernel regression 数据驱动的抗核回归
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-04-03 DOI: 10.1080/10485252.2024.2335494
Jianhua Zhou, Christopher F. Parmeter
{"title":"Data-driven resistant kernel regression","authors":"Jianhua Zhou, Christopher F. Parmeter","doi":"10.1080/10485252.2024.2335494","DOIUrl":"https://doi.org/10.1080/10485252.2024.2335494","url":null,"abstract":"We investigate data-driven bandwidth selection within the confines of robust (resistant) kernel smoothing. While several approaches presently exist, they require user defined robustness parameters....","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"25 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140576413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Enhanced doubly robust estimation with concave link functions for estimands in clinical trials 针对临床试验中的估算对象，利用凹链接函数增强双重稳健性估算
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2024-03-12 DOI: 10.1080/10485252.2024.2328078
Junyi Zhang, Ao Yuan, Ming T. Tan
{"title":"Enhanced doubly robust estimation with concave link functions for estimands in clinical trials","authors":"Junyi Zhang, Ao Yuan, Ming T. Tan","doi":"10.1080/10485252.2024.2328078","DOIUrl":"https://doi.org/10.1080/10485252.2024.2328078","url":null,"abstract":"For observational studies or clinical trials not fully randomised, the baseline covariates are often not balanced between the treatment and control groups. In this case, the traditional estimates o...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"131 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140148493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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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