A new nonparametric screening method for ultrahigh-dimensional survival data

DOI10.1016/j.csda.2017.10.003zbMath1469.62107OpenAlexW2766334444MaRDI QIDQ1662088

Jing Zhang, Xingqiu Zhao, Yan Yan Liu

Publication date: 17 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2017.10.003

zbMATH Keywords

variable screeningsure screening propertymodel-freeultrahigh-dimensional survival data

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items

Surrogate-variable-based model-free feature screening for survival data under the general censoring mechanism ⋮ Robust feature screening for high-dimensional survival data ⋮ A New Model-Free Feature Screening Procedure for Ultrahigh-Dimensional Interval-Censored Failure Time Data ⋮ Model‐free conditional screening for ultrahigh‐dimensional survival data via conditional distance correlation ⋮ Unnamed Item ⋮ The fused Kolmogorov-Smirnov screening for ultra-high dimensional semi-competing risks data ⋮ An efficient algorithm for joint feature screening in ultrahigh-dimensional Cox's model ⋮ Model pursuit and variable selection in the additive accelerated failure time model ⋮ Conditional screening for ultrahigh-dimensional survival data in case-cohort studies

Uses Software

• uniCox

Cites Work

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