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Independence index sufficient variable screening for categorical responses

Author

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  • Yuan, Qingcong
  • Chen, Xianyan
  • Ke, Chenlu
  • Yin, Xiangrong

Abstract

Variable screening is very popular in modern data analysis and is particularly useful for large p small n data. In this paper, a novel two-stage sufficient variable screening procedure, especially when the response is categorical is proposed. This procedure is very general and model-free, thus is robust against model mis-specification. In addition, the proposed procedure always improves existing screening approach in literature which only uses marginal relation. Asymptotic results and sure screening properties of the proposed methods are proved. Numerical studies and real data analysis are provided to demonstrate the advantages of the proposed method.

Suggested Citation

  • Yuan, Qingcong & Chen, Xianyan & Ke, Chenlu & Yin, Xiangrong, 2022. "Independence index sufficient variable screening for categorical responses," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:csdana:v:174:y:2022:i:c:s0167947322001104
    DOI: 10.1016/j.csda.2022.107530
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    References listed on IDEAS

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    Cited by:

    1. Ke, Chenlu & Yang, Wei & Yuan, Qingcong & Li, Lu, 2023. "Partial sufficient variable screening with categorical controls," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).

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