High-Dimensional Sparse Additive Hazards Regression
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DOI: 10.1080/01621459.2012.746068
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Cited by:
- Sokbae Lee & Myung Hwan Seo & Youngki Shin, 2016.
"The lasso for high dimensional regression with a possible change point,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 193-210, January.
- Sokbae (Simon) Lee & Myung Hwan Seo & Youngki Shin, 2014. "The lasso for high-dimensional regression with a possible change-point," CeMMAP working papers CWP26/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Sokbae (Simon) Lee & Myung Hwan Seo & Youngki Shin, 2014. "The lasso for high-dimensional regression with a possible change-point," CeMMAP working papers 26/14, Institute for Fiscal Studies.
- Zhang Haixiang & Zheng Yinan & Yoon Grace & Zhang Zhou & Gao Tao & Joyce Brian & Zhang Wei & Schwartz Joel & Vokonas Pantel & Colicino Elena & Baccarelli Andrea & Hou Lifang & Liu Lei, 2017. "Regularized estimation in sparse high-dimensional multivariate regression, with application to a DNA methylation study," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(3), pages 159-171, August.
- Yingying Fan & Jinchi Lv, 2013. "Asymptotic Equivalence of Regularization Methods in Thresholded Parameter Space," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 1044-1061, September.
- Yan, Xiaodong & Wang, Hongni & Wang, Wei & Xie, Jinhan & Ren, Yanyan & Wang, Xinjun, 2021. "Optimal model averaging forecasting in high-dimensional survival analysis," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1147-1155.
- Jianglin Fang, 2021. "Feature screening for ultrahigh-dimensional survival data when failure indicators are missing at random," Statistical Papers, Springer, vol. 62(3), pages 1141-1166, June.
- Qu, Lianqiang & Song, Xinyuan & Sun, Liuquan, 2018. "Identification of local sparsity and variable selection for varying coefficient additive hazards models," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 119-135.
- Xiaobo Wang & Jiayu Huang & Guosheng Yin & Jian Huang & Yuanshan Wu, 2023. "Double bias correction for high-dimensional sparse additive hazards regression with covariate measurement errors," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 115-141, January.
- Lv, Shaogao & You, Mengying & Lin, Huazhen & Lian, Heng & Huang, Jian, 2018. "On the sign consistency of the Lasso for the high-dimensional Cox model," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 79-96.
- Ai Ni & Jianwen Cai, 2018. "A regularized variable selection procedure in additive hazards model with stratified case-cohort design," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(3), pages 443-463, July.
- Ping-Shou Zhong & Tao Hu & Jun Li, 2015. "Tests for Coefficients in High-dimensional Additive Hazard Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 649-664, September.
- Yingying Fan & Jinchi Lv, 2014. "Asymptotic properties for combined L1 and concave regularization," Biometrika, Biometrika Trust, vol. 101(1), pages 57-70.
- Arfan Raheen Afzal & Jing Yang & Xuewen Lu, 2021. "Variable selection in partially linear additive hazards model with grouped covariates and a diverging number of parameters," Computational Statistics, Springer, vol. 36(2), pages 829-855, June.
- Xiaolin Chen & Yi Liu & Qihua Wang, 2019. "Joint feature screening for ultra-high-dimensional sparse additive hazards model by the sparsity-restricted pseudo-score estimator," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1007-1031, October.
- Jiang Dandan & Sun Jianguo, 2017. "Group Tests for High-dimensional Failure Time Data with the Additive Hazards Models," The International Journal of Biostatistics, De Gruyter, vol. 13(1), pages 1-10, May.
- Wang, Lu & Shen, Jincheng & Thall, Peter F., 2014. "A modified adaptive Lasso for identifying interactions in the Cox model with the heredity constraint," Statistics & Probability Letters, Elsevier, vol. 93(C), pages 126-133.
- Zemin Zheng & Jie Zhang & Yang Li, 2022. "L 0 -Regularized Learning for High-Dimensional Additive Hazards Regression," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2762-2775, September.
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