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Penalized Estimating Equations

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  • Wenjiang J. Fu

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  • Wenjiang J. Fu, 2003. "Penalized Estimating Equations," Biometrics, The International Biometric Society, vol. 59(1), pages 126-132, March.
    • Handle: RePEc:bla:biomet:v:59:y:2003:i:1:p:126-132
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    File URL: http://hdl.handle.net/10.1111/1541-0420.00015
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    References listed on IDEAS

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    1. Ke-Hai Yuan & Robert Jennrich, 2000. "Estimating Equations with Nuisance Parameters: Theory and Applications," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(2), pages 343-350, June.
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    Cited by:

    1. Zhang, Qiang & Ip, Edward H. & Pan, Junhao & Plemmons, Robert, 2017. "Individual-specific, sparse inverse covariance estimation in generalized estimating equations," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 96-103.
    2. Zhang, Hao Helen & Lu, Wenbin & Wang, Hansheng, 2010. "On sparse estimation for semiparametric linear transformation models," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1594-1606, August.
    3. Patrick J. Heagerty & Bryan A. Comstock, 2013. "Exploration of Lagged Associations using Longitudinal Data," Biometrics, The International Biometric Society, vol. 69(1), pages 197-205, March.
    4. Kelly Van Lancker & Oliver Dukes & Stijn Vansteelandt, 2023. "Ensuring valid inference for Cox hazard ratios after variable selection," Biometrics, The International Biometric Society, vol. 79(4), pages 3096-3110, December.
    5. Lan Wang & Jianhui Zhou & Annie Qu, 2012. "Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis," Biometrics, The International Biometric Society, vol. 68(2), pages 353-360, June.
    6. Tamar Sofer & Elizabeth D. Schifano & David C. Christiani & Xihong Lin, 2017. "Weighted pseudolikelihood for SNP set analysis with multiple secondary outcomes in case‐control genetic association studies," Biometrics, The International Biometric Society, vol. 73(4), pages 1210-1220, December.
    7. Fang, Jianglin, 2023. "A split-and-conquer variable selection approach for high-dimensional general semiparametric models with massive data," Journal of Multivariate Analysis, Elsevier, vol. 194(C).
    8. Lu Tang & Peter X.‐K. Song, 2021. "Poststratification fusion learning in longitudinal data analysis," Biometrics, The International Biometric Society, vol. 77(3), pages 914-928, September.
    9. Blommaert, A. & Hens, N. & Beutels, Ph., 2014. "Data mining for longitudinal data under multicollinearity and time dependence using penalized generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 667-680.
    10. Hu Yang & Chaohui Guo & Jing Lv, 2016. "Variable selection for generalized varying coefficient models with longitudinal data," Statistical Papers, Springer, vol. 57(1), pages 115-132, March.
    11. Davidov, Ori & Griskin, Vladimir, 2008. "A note on constrained estimation in the simple linear measurement error model," Statistics & Probability Letters, Elsevier, vol. 78(5), pages 508-517, April.
    12. Yang, Yuan & McMahan, Christopher S. & Wang, Yu-Bo & Ouyang, Yuyuan, 2024. "Estimation of l0 norm penalized models: A statistical treatment," Computational Statistics & Data Analysis, Elsevier, vol. 192(C).
    13. Peirong Xu & Lixing Zhu & Yi Li, 2014. "Ultrahigh dimensional time course feature selection," Biometrics, The International Biometric Society, vol. 70(2), pages 356-365, June.
    14. Li, Lexin & Yin, Xiangrong, 2009. "Longitudinal data analysis using sufficient dimension reduction method," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4106-4115, October.
    15. Li, Gaorong & Lian, Heng & Feng, Sanying & Zhu, Lixing, 2013. "Automatic variable selection for longitudinal generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 174-186.
    16. Geronimi, J. & Saporta, G., 2017. "Variable selection for multiply-imputed data with penalized generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 103-114.
    17. Ouyang, Jiangrong & Bondell, Howard, 2023. "Bayesian analysis of longitudinal data via empirical likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    18. Xingwei Tong & Xin He & Liuquan Sun & Jianguo Sun, 2009. "Variable Selection for Panel Count Data via Non‐Concave Penalized Estimating Function," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 620-635, December.
    19. Gregory Vaughan & Robert Aseltine & Kun Chen & Jun Yan, 2017. "Stagewise generalized estimating equations with grouped variables," Biometrics, The International Biometric Society, vol. 73(4), pages 1332-1342, December.
    20. Wang, Li & Wang, Suojin & Wang, Guannan, 2014. "Variable selection and estimation for longitudinal survey data," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 409-424.
    21. Brent A. Johnson & Qi Long & Matthias Chung, 2011. "On Path Restoration for Censored Outcomes," Biometrics, The International Biometric Society, vol. 67(4), pages 1379-1388, December.
    22. Fan, Yali & Qin, Guoyou & Zhu, Zhongyi, 2012. "Variable selection in robust regression models for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 156-167.

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