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Penalized Empirical Likelihood for the Sparse Cox Regression Model
The current penalized regression methods for selecting predictor variables and estimating the associated regression coefficients in the sparse Cox model are mainly based on partial likelihood. In this paper, a bias-corrected empirical likelihood method is proposed for the sparse Cox model in conjunc...
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| Pubblicato in: | J Stat Plan Inference |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6777733/ https://ncbi.nlm.nih.gov/pubmed/31588162 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jspi.2018.12.001 |
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