کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7546870 1489652 2016 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Adaptive kernel estimation of the baseline function in the Cox model with high-dimensional covariates
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آنالیز عددی
پیش نمایش صفحه اول مقاله
Adaptive kernel estimation of the baseline function in the Cox model with high-dimensional covariates
چکیده انگلیسی
We propose a novel kernel estimator of the baseline function in a general high-dimensional Cox model, for which we derive non-asymptotic rates of convergence. To construct our estimator, we first estimate the regression parameter in the Cox model via a LASSO procedure. We then plug this estimator into the classical kernel estimator of the baseline function, obtained by smoothing the so-called Breslow estimator of the cumulative baseline function. We propose and study an adaptive procedure for selecting the bandwidth, in the spirit of Goldenshluger and Lepski (2011). We state non-asymptotic oracle inequalities for the final estimator, which leads to a reduction in the rate of convergence when the dimension of the covariates grows.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multivariate Analysis - Volume 148, June 2016, Pages 141-159
نویسندگان
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