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High dimensional variable selection via tilting

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  • Haeran Cho
  • Piotr Fryzlewicz

Abstract

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Suggested Citation

  • Haeran Cho & Piotr Fryzlewicz, 2012. "High dimensional variable selection via tilting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 74(3), pages 593-622, June.
    • Handle: RePEc:bla:jorssb:v:74:y:2012:i:3:p:593-622
    DOI: j.1467-9868.2011.01023.x
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    File URL: http://hdl.handle.net/10.1111/j.1467-9868.2011.01023.x
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    Citations

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    Cited by:

    1. Baranowski, Rafal & Chen, Yining & Fryzlewicz, Piotr, 2020. "Ranking-based variable selection for high-dimensional data," LSE Research Online Documents on Economics 90233, London School of Economics and Political Science, LSE Library.
    2. Yundong Tu & Siwei Wang, 2023. "Variable Screening and Model Averaging for Expectile Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 574-598, June.
    3. Xiangyu Wang & Chenlei Leng, 2016. "High dimensional ordinary least squares projection for screening variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 589-611, June.
    4. Zhao, Bangxin & Liu, Xin & He, Wenqing & Yi, Grace Y., 2021. "Dynamic tilted current correlation for high dimensional variable screening," Journal of Multivariate Analysis, Elsevier, vol. 182(C).
    5. He, Kevin & Kang, Jian & Hong, Hyokyoung G. & Zhu, Ji & Li, Yanming & Lin, Huazhen & Xu, Han & Li, Yi, 2019. "Covariance-insured screening," Computational Statistics & Data Analysis, Elsevier, vol. 132(C), pages 100-114.
    6. Tu, Yundong & Wang, Siwei, 2020. "Jackknife model averaging for expectile regressions in increasing dimension," Economics Letters, Elsevier, vol. 197(C).
    7. Lan, Wei & Zhong, Ping-Shou & Li, Runze & Wang, Hansheng & Tsai, Chih-Ling, 2016. "Testing a single regression coefficient in high dimensional linear models," Journal of Econometrics, Elsevier, vol. 195(1), pages 154-168.
    8. Marc Robinson, 2014. "Connecting Evaluation and Budgeting," World Bank Publications - Books, The World Bank Group, number 18997, December.
    9. Lin, Lu & Sun, Jing, 2016. "Adaptive conditional feature screening," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 287-301.
    10. Li, Xingxiang & Cheng, Guosheng & Wang, Liming & Lai, Peng & Song, Fengli, 2017. "Ultrahigh dimensional feature screening via projection," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 88-104.
    11. Wanling Xie & Hu Yang, 2023. "Group sparse recovery via group square-root elastic net and the iterative multivariate thresholding-based algorithm," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 469-507, September.
    12. Randy C. S. Lai & Jan Hannig & Thomas C. M. Lee, 2015. "Generalized Fiducial Inference for Ultrahigh-Dimensional Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 760-772, June.
    13. Huiwen Wang & Ruiping Liu & Shanshan Wang & Zhichao Wang & Gilbert Saporta, 2020. "Ultra-high dimensional variable screening via Gram–Schmidt orthogonalization," Computational Statistics, Springer, vol. 35(3), pages 1153-1170, September.
    14. Zhou, Jingke & Zhu, Lixing, 2016. "Principal minimax support vector machine for sufficient dimension reduction with contaminated data," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 33-48.

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