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DC Field | Value | Language |
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dc.contributor.author | Li, E | - |
dc.contributor.author | Pan, J | - |
dc.contributor.author | Tang, M | - |
dc.contributor.author | Yu, K | - |
dc.contributor.author | Härdle, WK | - |
dc.contributor.author | Dai, X | - |
dc.contributor.author | Tian, M | - |
dc.date.accessioned | 2023-03-07T15:51:20Z | - |
dc.date.available | 2023-03-07T15:51:20Z | - |
dc.date.issued | 2023-03-08 | - |
dc.identifier | ORCID iDs: Erqian Li https://orcid.org/0000-0001-7327-1846; Man-lai Tang https://orcid.org/0000-0003-3934-2676; Keming Yu https://orcid.org/0000-0001-6341-8402; Wolfgang Karl Härdle https://orcid.org/0000-0001-5600-3014; Maozai Tian https://orcid.org/0000-0002-0515-4477 | - |
dc.identifier | 1295 | - |
dc.identifier.citation | Li, E. et al. (2023) ‘Weighted Competing Risks Quantile Regression Models and Variable Selection’, Mathematics, 11 (6), 1295, pp. 1 - 23. doi: 10.3390/math11061295. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/26077 | - |
dc.description | Data Availability Statement: Publicly available datasets were analyzed in this study. These data can be found here: 10.1038/bmt.2009.359. | - |
dc.description.abstract | Copyright © 2023 by the authors.The proportional subdistribution hazards (PSH) model is popularly used to deal with competing risks data. Censored quantile regression provides an important supplement as well as variable selection methods due to large numbers of irrelevant covariates in practice. In this paper, we study variable selection procedures based on penalized weighted quantile regression for competing risks models, which is conveniently applied by researchers. Asymptotic properties of the proposed estimators, including consistency and asymptotic normality of non-penalized estimator and consistency of variable selection, are established. Monte Carlo simulation studies are conducted, showing that the proposed methods are considerably stable and efficient. Real data about bone marrow transplant (BMT) are also analyzed to illustrate the application of the proposed procedure. | en_US |
dc.description.sponsorship | National Natural Science Funds of China (Grant No. 12101015), Scientific Research Foundation of North China University of Technology (No. 110051360002), the Fundamental Research Funds for Beijing Universities, NCUT (NO.110052971921/007), National Natural Science Foundation of China (No.11861042), and the China Statistical Research Project (No. 2020LZ25). | en_US |
dc.format.extent | 1 - 23 | - |
dc.language.iso | en_US | en_US |
dc.publisher | MDPI | en_US |
dc.rights | Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | competing risks | en_US |
dc.subject | cumulative incidence function | en_US |
dc.subject | bone marrow transplant | en_US |
dc.subject | re-distribution method | en_US |
dc.title | Weighted Competing Risks Quantile Regression Models and Variable Selection | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.3390/math11061295 | - |
dc.relation.isPartOf | Mathematics | - |
pubs.issue | 6 | - |
pubs.publication-status | Published | - |
pubs.volume | 11 | - |
dc.identifier.eissn | 2227-7390 | - |
dc.rights.holder | The authors | - |
Appears in Collections: | Dept of Mathematics Research Papers |
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