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Sparse Boosting for High-Dimensional Survival Data with Varying Coefficients
Motivated by high-throughput profiling studies in biomedical research, variable selection methods have been a focus for biostatisticians. In this paper we consider semiparametric varying-coefficient accelerated failure time models for right censored survival data with high-dimensional covariates. In...
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| Publié dans: | Stat Med |
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| Auteurs principaux: | , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
2017
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5799045/ https://ncbi.nlm.nih.gov/pubmed/29152776 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.7544 |
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