Adaptive estimation of the baseline hazard function in the Cox model by model selection, with high-dimensional covariates
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- 作者：Agathe Guillouxa ; agathe.guilloux@upmc.fr" class="auth_mail" title="E-mail the corresponding author ; Sarah Lemlerb ; sarah.lemler.pro@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Marie-Luce Taupinb ; c ; marie-luce.taupin@genopole.cnrs.fr" class="auth_mail" title="E-mail the corresponding author
- 关键词：Survival analysis ; Conditional hazard rate function ; Cox&rsquo ; s proportional hazards model ; Right-censored data ; Semi-parametric model ; Nonparametric model ; High-dimensional covariates ; Model selection ; Non-asymptotic oracle inequalities ; Concentration inequalities
- 刊名：Journal of Statistical Planning and Inference
- 出版年：2016
- 出版时间：April 2016
- 年：2016
- 卷：171
- 期：Complete
- 页码：38-62
- 全文大小：560 K
文摘
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Estimation of both parameters in the Cox’s model with high-dimensional covariates.
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Lasso procedure for the estimation of the regression parameter.
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Model selection for the estimation of the baseline function.
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Oracle inequality for the penalized contrast estimator of the baseline function.
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Study of the practical performances of the estimator of the baseline function.