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Weighted Wilcoxon-Type Smoothly Clipped Absolute Deviation Method

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  • Lan Wang
  • Runze Li

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  • Lan Wang & Runze Li, 2009. "Weighted Wilcoxon-Type Smoothly Clipped Absolute Deviation Method," Biometrics, The International Biometric Society, vol. 65(2), pages 564-571, June.
    • Handle: RePEc:bla:biomet:v:65:y:2009:i:2:p:564-571
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2008.01099.x
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    References listed on IDEAS

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    1. Hurvich, Clifford M. & Tsai, Chih-Ling, 1990. "Model selection for least absolute deviations regression in small samples," Statistics & Probability Letters, Elsevier, vol. 9(3), pages 259-265, March.
    2. Mahfoud, Ziyad R. & Randles, Ronald H., 2005. "Practical tests for randomized complete block designs," Journal of Multivariate Analysis, Elsevier, vol. 96(1), pages 73-92, September.
    3. Sin-Ho Jung, 2003. "Rank-based regression with repeated measurements data," Biometrika, Biometrika Trust, vol. 90(3), pages 732-740, September.
    4. You-Gan Wang & Yudong Zhao, 2008. "Weighted Rank Regression for Clustered Data Analysis," Biometrics, The International Biometric Society, vol. 64(1), pages 39-45, March.
    5. Wang, Hansheng & Li, Guodong & Jiang, Guohua, 2007. "Robust Regression Shrinkage and Consistent Variable Selection Through the LAD-Lasso," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 347-355, July.
    6. Terpstra, Jeff T. & McKean, Joseph W., 2005. "Rank-Based Analysis of Linear Models Using R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i07).
    7. Ronchetti, Elvezio, 1985. "Robust model selection in regression," Statistics & Probability Letters, Elsevier, vol. 3(1), pages 21-23, February.
    8. Somnath Datta & Glen A. Satten, 2008. "A Signed-Rank Test for Clustered Data," Biometrics, The International Biometric Society, vol. 64(2), pages 501-507, June.
    9. Bernard Rosner & Robert J. Glynn & Mei-Ling T. Lee, 2006. "Extension of the Rank Sum Test for Clustered Data: Two-Group Comparisons with Group Membership Defined at the Subunit Level," Biometrics, The International Biometric Society, vol. 62(4), pages 1251-1259, December.
    10. Zhezhen Jin, 2003. "Rank-based inference for the accelerated failure time model," Biometrika, Biometrika Trust, vol. 90(2), pages 341-353, June.
    11. Bernard Rosner & Robert J. Glynn & Mei-Ling T. Lee, 2006. "The Wilcoxon Signed Rank Test for Paired Comparisons of Clustered Data," Biometrics, The International Biometric Society, vol. 62(1), pages 185-192, March.
    12. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
    13. Heller, Glenn, 2007. "Smoothed Rank Regression With Censored Data," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 552-559, June.
    14. Wisnowski, James W. & Simpson, James R. & Montgomery, Douglas C. & Runger, George C., 2003. "Resampling methods for variable selection in robust regression," Computational Statistics & Data Analysis, Elsevier, vol. 43(3), pages 341-355, July.
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    Cited by:

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    2. Jiaming Luan & Hongwei Wang & Kangning Wang & Benle Zhang, 2022. "Robust distributed estimation and variable selection for massive datasets via rank regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(3), pages 435-450, June.
    3. Long Feng & Changliang Zou & Zhaojun Wang & Xianwu Wei & Bin Chen, 2015. "Robust spline-based variable selection in varying coefficient model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(1), pages 85-118, January.
    4. Gijbels, I. & Vrinssen, I., 2015. "Robust nonnegative garrote variable selection in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 85(C), pages 1-22.
    5. Smucler, Ezequiel & Yohai, Victor J., 2017. "Robust and sparse estimators for linear regression models," Computational Statistics & Data Analysis, Elsevier, vol. 111(C), pages 116-130.
    6. Yang, Hu & Guo, Chaohui & Lv, Jing, 2015. "SCAD penalized rank regression with a diverging number of parameters," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 321-333.
    7. Yuyang Liu & Pengfei Pi & Shan Luo, 2023. "A semi-parametric approach to feature selection in high-dimensional linear regression models," Computational Statistics, Springer, vol. 38(2), pages 979-1000, June.
    8. Liya Fu & Zhuoran Yang & Fengjing Cai & You-Gan Wang, 2021. "Efficient and doubly-robust methods for variable selection and parameter estimation in longitudinal data analysis," Computational Statistics, Springer, vol. 36(2), pages 781-804, June.
    9. Zhang, Qingzhao & Duan, Xiaogang & Ma, Shuangge, 2017. "Focused information criterion and model averaging with generalized rank regression," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 11-19.

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