Pub Date : 2024-08-04DOI: 10.1080/10485252.2024.2387091
Xia Cai, Yaru Qiao, Jiahua Qiao, Liang Yan
Generalized extreme value (GEV) distribution is used to analyse the maximum from a block of data. It is very useful to describe the unusual event rather than the usual event. In this paper, we prop...
{"title":"Generalized fiducial inference for the GEV change-point model","authors":"Xia Cai, Yaru Qiao, Jiahua Qiao, Liang Yan","doi":"10.1080/10485252.2024.2387091","DOIUrl":"https://doi.org/10.1080/10485252.2024.2387091","url":null,"abstract":"Generalized extreme value (GEV) distribution is used to analyse the maximum from a block of data. It is very useful to describe the unusual event rather than the usual event. In this paper, we prop...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"28 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947920","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}
Pub Date : 2024-07-30DOI: 10.1080/10485252.2024.2383772
Xiaogang Wang, Han Wang, Feipeng Zhang, Caiyun Fan
This paper considers a linear-quadratic Tobit regression model, which is developed for modelling the mixture structure with a line segment and a quadratic segment intersecting at an unknown change ...
{"title":"Linear-quadratic Tobit regression model with a change point due to a covariate threshold","authors":"Xiaogang Wang, Han Wang, Feipeng Zhang, Caiyun Fan","doi":"10.1080/10485252.2024.2383772","DOIUrl":"https://doi.org/10.1080/10485252.2024.2383772","url":null,"abstract":"This paper considers a linear-quadratic Tobit regression model, which is developed for modelling the mixture structure with a line segment and a quadratic segment intersecting at an unknown change ...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"374 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947921","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}
Pub Date : 2024-07-30DOI: 10.1080/10485252.2024.2383307
Fei Tan, Xiaofeng Zhao, Hanxiang Peng
The uniform and the statistical leverage-scores-based (nonuniform) distributions are often used in the development of randomised algorithms and the analysis of data of massive size. Both distributi...
{"title":"The A-optimal subsampling approach to the analysis of count data of massive size","authors":"Fei Tan, Xiaofeng Zhao, Hanxiang Peng","doi":"10.1080/10485252.2024.2383307","DOIUrl":"https://doi.org/10.1080/10485252.2024.2383307","url":null,"abstract":"The uniform and the statistical leverage-scores-based (nonuniform) distributions are often used in the development of randomised algorithms and the analysis of data of massive size. Both distributi...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"44 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947923","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}
Pub Date : 2024-07-30DOI: 10.1080/10485252.2024.2384608
Chen Zhong
The kernel distribution estimator (KDE) is proposed based on residuals of the innovation distribution in the autoregressive moving-average (ARMA) time series. The deviation between KDE and the inno...
{"title":"Statistical inference for innovation distribution in ARMA and multi-step-ahead prediction via empirical process","authors":"Chen Zhong","doi":"10.1080/10485252.2024.2384608","DOIUrl":"https://doi.org/10.1080/10485252.2024.2384608","url":null,"abstract":"The kernel distribution estimator (KDE) is proposed based on residuals of the innovation distribution in the autoregressive moving-average (ARMA) time series. The deviation between KDE and the inno...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"374 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947925","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}
Pub Date : 2024-07-25DOI: 10.1080/10485252.2024.2376089
Kadir Karakaya, Sümeyra Sert, Ihab Abusaif, Coşkun Kuş, Hon Keung Tony Ng, Haikady N. Nagaraja
In this paper, a new class of distribution-free statistics based on order statistics from two independent samples is introduced to test the equality of two continuous distributions. The null distri...
{"title":"A class of nonparametric tests for the two-sample problem based on order statistics","authors":"Kadir Karakaya, Sümeyra Sert, Ihab Abusaif, Coşkun Kuş, Hon Keung Tony Ng, Haikady N. Nagaraja","doi":"10.1080/10485252.2024.2376089","DOIUrl":"https://doi.org/10.1080/10485252.2024.2376089","url":null,"abstract":"In this paper, a new class of distribution-free statistics based on order statistics from two independent samples is introduced to test the equality of two continuous distributions. The null distri...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"108 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141776354","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}
Pub Date : 2024-07-24DOI: 10.1080/10485252.2024.2378897
Jeong Min Jeon
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...
{"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}
Pub Date : 2024-07-24DOI: 10.1080/10485252.2024.2378904
Yong Wang, Reza Modarres
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...
{"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}
Pub Date : 2024-07-09DOI: 10.1080/10485252.2024.2368631
Enze Shi, Jinhan Xie, Shenggang Hu, Ke Sun, Hongsheng Dai, Bei Jiang, Linglong Kong, Lingzhu Li
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 ...
{"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}
Pub Date : 2024-07-03DOI: 10.1080/10485252.2024.2371524
Dongxiao Han, Miao Han, Meiling Hao, Liuquan Sun, Siyang Wang
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...
{"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}
Pub Date : 2024-06-18DOI: 10.1080/10485252.2024.2366978
Daoji Li, Yinfei Kong, Dawit Zerom
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...
{"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}
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