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5. Penalized empirical likelihood inference for sparse additive hazards regression with a divergent num

Penalized empirical likelihood inference for sparse additive hazards regression with a divergent num

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：dingxyz

【摘 要】

：

High-dimensional sparse modelling with censored survival data is of great practical importance,as exemplified by applications in high-throughput genomic data analysis.

【作 者】

：

Shanshan Wang Liming Xiang 

【机 构】

：

School of Economics and Management,Beihang University,Beijing 100191,China;School of Physical and Ma

【出 处】

：

上海交通大学

【发表日期】

：

2016年4期

【关键词】

：

Penalized empirical likelihood Empirical likelihood ratio Oracle property Smooth 

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　　High-dimensional sparse modelling with censored survival data is of great practical importance,as exemplified by applications in high-throughput genomic data analysis.

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