References in zbMATH (referenced in 12 articles )

Showing results 1 to 12 of 12.
Sorted by year (citations)

  1. Lin, Yuanyuan; Liu, Xianhui; Hao, Meiling: Model-free feature screening for high-dimensional survival data (2018)
  2. Liu, Yanyan; Zhang, Jing; Zhao, Xingqiu: A new nonparametric screening method for ultrahigh-dimensional survival data (2018)
  3. Zhang, Jing; Yin, Guosheng; Liu, Yanyan; Wu, Yuanshan: Censored cumulative residual independent screening for ultrahigh-dimensional survival data (2018)
  4. Hong, Hyokyoung Grace; Li, Yi: Feature selection of ultrahigh-dimensional covariates with survival outcomes: a selective review (2017)
  5. Lee, Kyu Ha; Chakraborty, Sounak; Sun, Jianguo: Variable selection for high-dimensional genomic data with censored outcomes using group lasso prior (2017)
  6. Kaneko, Shuhei; Hirakawa, Akihiro; Hamada, Chikuma: Enhancing the lasso approach for developing a survival prediction model based on gene expression data (2015)
  7. Xu, Jinfeng: High-dimensional Cox regression analysis in genetic studies with censored survival outcomes (2012)
  8. Zhao, Sihai Dave; Li, Yi: Principled sure independence screening for Cox models with ultra-high-dimensional covariates (2012)
  9. Chakraborty, Sounak; Guo, Ruixin: A Bayesian hybrid huberized support vector machine and its applications in high-dimensional medical data (2011)
  10. Benner, Axel; Zucknick, Manuela; Hielscher, Thomas; Ittrich, Carina; Mansmann, Ulrich: High-dimensional Cox models: The choice of penalty as part of the model building process (2010)
  11. Schifano, Elizabeth D.; Strawderman, Robert L.; Wells, Martin T.: Majorization-minimization algorithms for nonsmoothly penalized objective functions (2010)
  12. Tibshirani, Robert J.: Univariate shrinkage in the Cox model for high dimensional data (2009)