A fast divide-and-conquer sparse Cox regression.

We propose a computationally and statistically efficient divide-and-conquer (DAC) algorithm to fit sparse Cox regression to massive datasets where the sample size $n_0$ is exceedingly large and the covariate dimension $p$ is not small but $n_0\gg p$. The proposed algorithm achieves computational eff...

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Detalles Bibliográficos
Publicado en:Biostatistics Vol. 22; no. 2; pp. 381 - 402
Autores principales: Wang, Yan, Hong, Chuan, Palmer, Nathan, Di, Qian, Schwartz, Joel, Kohane, Isaac, Cai, Tianxi
Formato: research Journal Article
Publicado: Oxford University Press / USA Apr2021
Acceso en línea:Ver este registro en EBSCOhost