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Robust conditional nonparametric independence screening for ultrahigh-dimensional data

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  • Zhang, Shucong
  • Pan, Jing
  • Zhou, Yong

Abstract

This article novelly proposes a robust model-free screening procedure, which performs well for a variety of semivarying coefficient models. Under technical conditions, we show that it possesses the ranking consistency property and the sure screening property. Comprehensive simulation studies are conducted to demonstrate that it exhibits more competitive performance than existing screening methods.

Suggested Citation

  • Zhang, Shucong & Pan, Jing & Zhou, Yong, 2018. "Robust conditional nonparametric independence screening for ultrahigh-dimensional data," Statistics & Probability Letters, Elsevier, vol. 143(C), pages 95-101.
    • Handle: RePEc:eee:stapro:v:143:y:2018:i:c:p:95-101
    DOI: 10.1016/j.spl.2018.08.003
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    References listed on IDEAS

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    1. Jingyuan Liu & Runze Li & Rongling Wu, 2014. "Feature Selection for Varying Coefficient Models With Ultrahigh-Dimensional Covariates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 266-274, March.
    2. Runze Li & Wei Zhong & Liping Zhu, 2012. "Feature Screening via Distance Correlation Learning," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(499), pages 1129-1139, September.
    3. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
    4. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
    5. Fan, Jianqing & Feng, Yang & Song, Rui, 2011. "Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 544-557.
    6. Jianqing Fan & Yunbei Ma & Wei Dai, 2014. "Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1270-1284, September.
    7. Jianqing Fan & Jinchi Lv, 2008. "Sure independence screening for ultrahigh dimensional feature space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 849-911, November.
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