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Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent

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Cited by:

  1. Das Ujjwal & Ebrahimi Nader, 2018. "A New Method For Covariate Selection In Cox Model," Statistics in Transition New Series, Statistics Poland, vol. 19(2), pages 297-314, June.
  2. S. E. Hill, 2022. "In-game win probability models for Canadian football," Journal of Business Analytics, Taylor & Francis Journals, vol. 5(2), pages 164-178, July.
  3. Jie Xiong & Zhitong Bing & Yanlin Su & Defeng Deng & Xiaoning Peng, 2014. "An Integrated mRNA and microRNA Expression Signature for Glioblastoma Multiforme Prognosis," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-8, May.
  4. repec:jss:jstsof:47:i09 is not listed on IDEAS
  5. Yoonsuh Jung, 2018. "Multiple predicting K-fold cross-validation for model selection," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 197-215, January.
  6. Willems, S.J.W. & Fiocco, M. & Meulman, J.J., 2017. "Optimal scaling for survival analysis with ordinal data," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 155-171.
  7. Sill, Martin & Hielscher, Thomas & Becker, Natalia & Zucknick, Manuela, 2014. "c060: Extended Inference with Lasso and Elastic-Net Regularized Cox and Generalized Linear Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 62(i05).
  8. Haixiang Zhang & Jian Huang & Liuquan Sun, 2022. "Projection‐based and cross‐validated estimation in high‐dimensional Cox model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 353-372, March.
  9. Jonas Krampe & Efstathios Paparoditis, 2021. "Sparsity concepts and estimation procedures for high‐dimensional vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 554-579, September.
  10. Saverio Ranciati & Giuliano Galimberti & Gabriele Soffritti, 2019. "Bayesian variable selection in linear regression models with non-normal errors," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(2), pages 323-358, June.
  11. Guido Imbens & Nathan Kallus & Xiaojie Mao & Yuhao Wang, 2022. "Long-term Causal Inference Under Persistent Confounding via Data Combination," Papers 2202.07234, arXiv.org, revised Aug 2024.
  12. Ascarza, & Neslin, & Netzer, & Lemmens, Aurélie & Anderson, Zachery & Fader, Peter S. & Gupta, S. & Hardie, B.G.S. & Libai, Barak & Neal, David & Provost, Foster, 2018. "In pursuit of enhanced customer retention management : Review, key issues, and future directions," Other publications TiSEM 28a90d28-6daf-42f1-bd8e-e, Tilburg University, School of Economics and Management.
  13. Kou Fujimori, 2022. "The variable selection by the Dantzig selector for Cox’s proportional hazards model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(3), pages 515-537, June.
  14. Bommert, Andrea & Sun, Xudong & Bischl, Bernd & Rahnenführer, Jörg & Lang, Michel, 2020. "Benchmark for filter methods for feature selection in high-dimensional classification data," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
  15. Jacek Bia{l}ek & Maciej Berk{e}sewicz, 2020. "Scanner data in inflation measurement: from raw data to price indices," Papers 2005.11233, arXiv.org.
  16. Liao Zhu & Sumanta Basu & Robert A. Jarrow & Martin T. Wells, 2020. "High-Dimensional Estimation, Basis Assets, and the Adaptive Multi-Factor Model," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 10(04), pages 1-52, December.
  17. Rafael Blanquero & Emilio Carrizosa & Pepa Ramírez-Cobo & M. Remedios Sillero-Denamiel, 2021. "A cost-sensitive constrained Lasso," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(1), pages 121-158, March.
  18. Kevin He & Yue Wang & Xiang Zhou & Han Xu & Can Huang, 2019. "An improved variable selection procedure for adaptive Lasso in high-dimensional survival analysis," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 569-585, July.
  19. Ye-Lin Liang & Yuan Zhang & Xi-Rong Tan & Han Qiao & Song-Ran Liu & Ling-Long Tang & Yan-Ping Mao & Lei Chen & Wen-Fei Li & Guan-Qun Zhou & Yin Zhao & Jun-Yan Li & Qian Li & Sheng-Yan Huang & Sha Gong, 2022. "A lncRNA signature associated with tumor immune heterogeneity predicts distant metastasis in locoregionally advanced nasopharyngeal carcinoma," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  20. Rutzer, Christian & Niggli, Matthias & Weder, Rolf, 2020. "Estimating the Green Potential of Occupations: A New Approach Applied to the U.S. Labor Market," Working papers 2020/03, Faculty of Business and Economics - University of Basel.
  21. Zhixuan Fu & Chirag R. Parikh & Bingqing Zhou, 2017. "Penalized variable selection in competing risks regression," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 353-376, July.
  22. Marija Pizurica & Yuanning Zheng & Francisco Carrillo-Perez & Humaira Noor & Wei Yao & Christian Wohlfart & Antoaneta Vladimirova & Kathleen Marchal & Olivier Gevaert, 2024. "Digital profiling of gene expression from histology images with linearized attention," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  23. Andreea L. Erciulescu & Jean D. Opsomer, 2022. "A model‐based approach to predict employee compensation components," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1503-1520, November.
  24. Soave, David & Lawless, Jerald F., 2023. "Regularized regression for two phase failure time studies," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
  25. Reid, Stephen & Tibshirani, Rob, 2014. "Regularization Paths for Conditional Logistic Regression: The clogitL1 Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i12).
  26. David Rossell & Oriol Abril & Anirban Bhattacharya, 2021. "Approximate Laplace approximations for scalable model selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 853-879, September.
  27. Shengzhi Huang & Jiajia Qian & Yong Huang & Wei Lu & Yi Bu & Jinqing Yang & Qikai Cheng, 2022. "Disclosing the relationship between citation structure and future impact of a publication," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(7), pages 1025-1042, July.
  28. Li, Libo, 2018. "Predicting online invitation responses with a competing risk model using privacy-friendly social event data," European Journal of Operational Research, Elsevier, vol. 270(2), pages 698-708.
  29. Ling Zhou & Lu Tang & Angela T. Song & Diane M. Cibrik & Peter X.-K. Song, 2017. "A LASSO Method to Identify Protein Signature Predicting Post-transplant Renal Graft Survival," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 431-452, December.
  30. Aaron J. Molstad & Rohit K. Patra, 2023. "Dimension reduction for integrative survival analysis," Biometrics, The International Biometric Society, vol. 79(3), pages 1610-1623, September.
  31. Ethan Mark & David Goldsman & Brian Gurbaxani & Pinar Keskinocak & Joel Sokol, 2019. "Using machine learning and an ensemble of methods to predict kidney transplant survival," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-13, January.
  32. Robert A. Jarrow & Rinald Murataj & Martin T. Wells & Liao Zhu, 2023. "The Low-Volatility Anomaly And The Adaptive Multi-Factor Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 26(04n05), pages 1-33, August.
  33. Kotaro Ishizu & Shosuke Nishimoto & Yutaro Ueoka & Akihiro Funamizu, 2024. "Localized and global representation of prior value, sensory evidence, and choice in male mouse cerebral cortex," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
  34. Hua Xin & Yuhlong Lio & Hsien-Ching Chen & Tzong-Ru Tsai, 2024. "Zero-Inflated Binary Classification Model with Elastic Net Regularization," Mathematics, MDPI, vol. 12(19), pages 1-17, September.
  35. Liao Zhu & Robert A. Jarrow & Martin T. Wells, 2021. "Time-Invariance Coefficients Tests with the Adaptive Multi-Factor Model," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-30, December.
  36. Paul Ghelasi & Florian Ziel, 2024. "From day-ahead to mid and long-term horizons with econometric electricity price forecasting models," Papers 2406.00326, arXiv.org, revised Aug 2024.
  37. Jonathan Fuhr & Philipp Berens & Dominik Papies, 2024. "Estimating Causal Effects with Double Machine Learning -- A Method Evaluation," Papers 2403.14385, arXiv.org, revised Apr 2024.
  38. Rutzer, Christian & Niggli, Matthias, 2020. "Environmental Policy and Heterogeneous Labor Market Effects: Evidence from Europe," Working papers 2020/09, Faculty of Business and Economics - University of Basel.
  39. Takumi Saegusa & Tianzhou Ma & Gang Li & Ying Qing Chen & Mei-Ling Ting Lee, 2020. "Variable Selection in Threshold Regression Model with Applications to HIV Drug Adherence Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 376-398, December.
  40. 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.
  41. Zhixuan Fu & Shuangge Ma & Haiqun Lin & Chirag R. Parikh & Bingqing Zhou, 2017. "Penalized Variable Selection for Multi-center Competing Risks Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 379-405, December.
  42. Matthew F. Dixon & Nicholas G. Polson & Kemen Goicoechea, 2022. "Deep Partial Least Squares for Empirical Asset Pricing," Papers 2206.10014, arXiv.org.
  43. Li, Jianbo & Gu, Minggao & Zhang, Riquan, 2013. "Variable selection for general transformation models with right censored data via nonconcave penalties," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 445-456.
  44. Karthik Bharath & Sebastian Kurtek & Arvind Rao & Veerabhadran Baladandayuthapani, 2018. "Radiologic image‐based statistical shape analysis of brain tumours," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1357-1378, November.
  45. Barbarino, Alessandro & Bura, Efstathia, 2024. "Forecasting Near-equivalence of Linear Dimension Reduction Methods in Large Panels of Macro-variables," Econometrics and Statistics, Elsevier, vol. 31(C), pages 1-18.
  46. Simon Bussy & Mokhtar Z. Alaya & Anne‐Sophie Jannot & Agathe Guilloux, 2022. "Binacox: automatic cut‐point detection in high‐dimensional Cox model with applications in genetics," Biometrics, The International Biometric Society, vol. 78(4), pages 1414-1426, December.
  47. Vincent Loubiere & Bernardo P. Almeida & Michaela Pagani & Alexander Stark, 2024. "Developmental and housekeeping transcriptional programs display distinct modes of enhancer-enhancer cooperativity in Drosophila," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  48. Shikhar Uttam & Andrew M. Stern & Christopher J. Sevinsky & Samantha Furman & Filippo Pullara & Daniel Spagnolo & Luong Nguyen & Albert Gough & Fiona Ginty & D. Lansing Taylor & S. Chakra Chennubhotla, 2020. "Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
  49. Ujjwal Das & Nader Ebrahimi, 2018. "A New Method For Covariate Selection In Cox Model," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 297-314, June.
  50. Wei Zhang & Takayo Ota & Viji Shridhar & Jeremy Chien & Baolin Wu & Rui Kuang, 2013. "Network-based Survival Analysis Reveals Subnetwork Signatures for Predicting Outcomes of Ovarian Cancer Treatment," PLOS Computational Biology, Public Library of Science, vol. 9(3), pages 1-16, March.
  51. Wu, Tong Tong & He, Xin, 2012. "Coordinate ascent for penalized semiparametric regression on high-dimensional panel count data," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 25-33, January.
  52. Wenhua Liang & Jianhua Yao & Ailan Chen & Qingquan Lv & Mark Zanin & Jun Liu & SookSan Wong & Yimin Li & Jiatao Lu & Hengrui Liang & Guoqiang Chen & Haiyan Guo & Jun Guo & Rong Zhou & Limin Ou & Niyun, 2020. "Early triage of critically ill COVID-19 patients using deep learning," Nature Communications, Nature, vol. 11(1), pages 1-7, December.
  53. Biagini, Francesca & Groll, Andreas & Widenmann, Jan, 2013. "Intensity-based premium evaluation for unemployment insurance products," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 302-316.
  54. Benedicte Sjo Tislevoll & Monica Hellesøy & Oda Helen Eck Fagerholt & Stein-Erik Gullaksen & Aashish Srivastava & Even Birkeland & Dimitrios Kleftogiannis & Pilar Ayuda-Durán & Laure Piechaczyk & Dagi, 2023. "Early response evaluation by single cell signaling profiling in acute myeloid leukemia," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
  55. Matthew F Dixon, 2017. "Sequence Classification of the Limit Order Book using Recurrent Neural Networks," Papers 1707.05642, arXiv.org.
  56. Tatyana Deryugina & Garth Heutel & Nolan H. Miller & David Molitor & Julian Reif, 2019. "The Mortality and Medical Costs of Air Pollution: Evidence from Changes in Wind Direction," American Economic Review, American Economic Association, vol. 109(12), pages 4178-4219, December.
  57. Gal Dinstag & David Amar & Erik Ingelsson & Euan Ashley & Ron Shamir, 2019. "Personalized prediction of adverse heart and kidney events using baseline and longitudinal data from SPRINT and ACCORD," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-12, August.
  58. Maciej Berk{e}sewicz & Greta Bia{l}kowska & Krzysztof Marcinkowski & Magdalena Ma'slak & Piotr Opiela & Robert Pater & Katarzyna Zadroga, 2019. "Enhancing the Demand for Labour survey by including skills from online job advertisements using model-assisted calibration," Papers 1908.06731, arXiv.org.
  59. Shuang Huang & Chengcheng Hu & Melanie L. Bell & Dean Billheimer & Stefano Guerra & Denise Roe & Monica M. Vasquez & Edward J. Bedrick, 2018. "Regularized continuous‐time Markov Model via elastic net," Biometrics, The International Biometric Society, vol. 74(3), pages 1045-1054, September.
  60. Andreas Groll & Gerhard Tutz, 2017. "Variable selection in discrete survival models including heterogeneity," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 305-338, April.
  61. Thierry Chekouo & Francesco C. Stingo & James D. Doecke & Kim-Anh Do, 2017. "A Bayesian integrative approach for multi-platform genomic data: A kidney cancer case study," Biometrics, The International Biometric Society, vol. 73(2), pages 615-624, June.
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