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Model-free conditional screening via conditional distance correlation

Author

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  • Jun Lu

    (Shandong University)

  • Lu Lin

    (Shandong University
    School of Statistics, Qufu Normal University)

Abstract

With the knowledge on the predetermined active predictors, we develop a feature screening procedure via the conditional distance correlation learning. The proposed procedure can significantly lower the correlation among the predictors when they are highly correlated and thus reduce the numbers of false positive and false negative. Meanwhile, when the conditional set is unable to be accessed beforehand, a data-driven method is provided to select it. We establish both the ranking consistency and the sure screening property for the new proposed procedure. To compare the performance of our method with its competitors, extensive simulations are conducted, which shows that the new procedure performs well in both the linear and nonlinear models. Finally, a real data analysis is investigated to further illustrate the effectiveness of the new method.

Suggested Citation

  • Jun Lu & Lu Lin, 2020. "Model-free conditional screening via conditional distance correlation," Statistical Papers, Springer, vol. 61(1), pages 225-244, February.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:1:d:10.1007_s00362-017-0931-7
    DOI: 10.1007/s00362-017-0931-7
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    References listed on IDEAS

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    Cited by:

    1. Jing Zhang & Haibo Zhou & Yanyan Liu & Jianwen Cai, 2021. "Conditional screening for ultrahigh-dimensional survival data in case-cohort studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(4), pages 632-661, October.
    2. Shuaishuai Chen & Jun Lu, 2023. "Quantile-Composited Feature Screening for Ultrahigh-Dimensional Data," Mathematics, MDPI, vol. 11(10), pages 1-21, May.
    3. Jun Lu & Dan Wang & Qinqin Hu, 2022. "Interaction screening via canonical correlation," Computational Statistics, Springer, vol. 37(5), pages 2637-2670, November.
    4. Jing Zhang & Yanyan Liu & Hengjian Cui, 2021. "Model-free feature screening via distance correlation for ultrahigh dimensional survival data," Statistical Papers, Springer, vol. 62(6), pages 2711-2738, December.

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