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Interaction screening via canonical correlation

Author

Listed:
  • Jun Lu

    (National University of Defense Technology)

  • Dan Wang

    (National University of Defense Technology)

  • Qinqin Hu

    (Shandong University)

Abstract

A new canonical correlation (CC) based interaction screening procedure called CCIS is suggested for the ultrahigh dimensional interaction model with a multivariate response. The CCIS procedure consists of two steps: First, it selects a set of candidate features which has a large CC with the squared response; Then it recovers the influential main effects and interactions simultaneously from the reduced interaction model built by the features selected in the first step. CCIS has a ranking statistic with a simple structure, thus it can be calculated very quickly. More importantly, CCIS is powerful to detect the features which have a linear relationship with the response. Both theoretical results and numerical studies are provided to illustrate the effectiveness of CCIS.

Suggested Citation

  • Jun Lu & Dan Wang & Qinqin Hu, 2022. "Interaction screening via canonical correlation," Computational Statistics, Springer, vol. 37(5), pages 2637-2670, November.
    • Handle: RePEc:spr:compst:v:37:y:2022:i:5:d:10.1007_s00180-022-01206-7
    DOI: 10.1007/s00180-022-01206-7
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    References listed on IDEAS

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