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Sparse quantile regression via ℓ０-penalty

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  • HONDA, Toshio
  • 本田, 敏雄

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Suggested Citation

  • HONDA, Toshio & 本田, 敏雄, 2023. "Sparse quantile regression via ℓ０-penalty," Discussion Papers 2023-03, Graduate School of Economics, Hitotsubashi University.
    • Handle: RePEc:hit:econdp:2023-03
    Note: The first version : November 2023, This version : December 2023
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    References listed on IDEAS

    as
    1. Jiahua Chen & Zehua Chen, 2008. "Extended Bayesian information criteria for model selection with large model spaces," Biometrika, Biometrika Trust, vol. 95(3), pages 759-771.
    2. Chen, Le-Yu & Lee, Sokbae, 2023. "Sparse quantile regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2195-2217.
    3. Eun Ryung Lee & Hohsuk Noh & Byeong U. Park, 2014. "Model Selection via Bayesian Information Criterion for Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 216-229, March.
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    More about this item

    Keywords

    selection consistency; high-dimensional information criteria; B-spline basis; additive models; varying coefficient models;
    All these keywords.

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