Sure Independence Screening for Ultrahigh-Dimensional Additive Model with Multivariate Response
This paper investigated an ultrahigh-dimensional feature screening approach for additive models with multivariate responses. We proposed a nonparametric screening procedure based on random vector correlations between each predictor and multivariate response, and we established the theoretical result...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/10/1558 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849326818329362432 |
|---|---|
| author | Yongshuai Chen Baosheng Liang |
| author_facet | Yongshuai Chen Baosheng Liang |
| author_sort | Yongshuai Chen |
| collection | DOAJ |
| description | This paper investigated an ultrahigh-dimensional feature screening approach for additive models with multivariate responses. We proposed a nonparametric screening procedure based on random vector correlations between each predictor and multivariate response, and we established the theoretical results of sure screening and ranking consistency properties under regularity conditions. We also developed an iterative sure independence screening algorithm for convenient and efficient implementation. Extensive finite-sample simulations and a real data example demonstrate the superiority of the proposed procedure over 58–100% of existing candidates. On average, the proposed method outperforms 79% of existing methods across all scenarios considered. |
| format | Article |
| id | doaj-art-ff4ff03dca4a4db18ed780439225fadf |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-ff4ff03dca4a4db18ed780439225fadf2025-08-20T03:48:02ZengMDPI AGMathematics2227-73902025-05-011310155810.3390/math13101558Sure Independence Screening for Ultrahigh-Dimensional Additive Model with Multivariate ResponseYongshuai Chen0Baosheng Liang1School of Statistics, Capital University of Economics and Business, Beijing 100070, ChinaDepartment of Biostatistics, School of Public Health, Peking University, Beijing 100191, ChinaThis paper investigated an ultrahigh-dimensional feature screening approach for additive models with multivariate responses. We proposed a nonparametric screening procedure based on random vector correlations between each predictor and multivariate response, and we established the theoretical results of sure screening and ranking consistency properties under regularity conditions. We also developed an iterative sure independence screening algorithm for convenient and efficient implementation. Extensive finite-sample simulations and a real data example demonstrate the superiority of the proposed procedure over 58–100% of existing candidates. On average, the proposed method outperforms 79% of existing methods across all scenarios considered.https://www.mdpi.com/2227-7390/13/10/1558sure independence screeningultrahigh dimensionaladditive modelmultivariate responserandom vector correlation |
| spellingShingle | Yongshuai Chen Baosheng Liang Sure Independence Screening for Ultrahigh-Dimensional Additive Model with Multivariate Response Mathematics sure independence screening ultrahigh dimensional additive model multivariate response random vector correlation |
| title | Sure Independence Screening for Ultrahigh-Dimensional Additive Model with Multivariate Response |
| title_full | Sure Independence Screening for Ultrahigh-Dimensional Additive Model with Multivariate Response |
| title_fullStr | Sure Independence Screening for Ultrahigh-Dimensional Additive Model with Multivariate Response |
| title_full_unstemmed | Sure Independence Screening for Ultrahigh-Dimensional Additive Model with Multivariate Response |
| title_short | Sure Independence Screening for Ultrahigh-Dimensional Additive Model with Multivariate Response |
| title_sort | sure independence screening for ultrahigh dimensional additive model with multivariate response |
| topic | sure independence screening ultrahigh dimensional additive model multivariate response random vector correlation |
| url | https://www.mdpi.com/2227-7390/13/10/1558 |
| work_keys_str_mv | AT yongshuaichen sureindependencescreeningforultrahighdimensionaladditivemodelwithmultivariateresponse AT baoshengliang sureindependencescreeningforultrahighdimensionaladditivemodelwithmultivariateresponse |