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Journal of Computational and Graphical Statistics Volume 23, 2014 - Issue 4
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ARTICLES: Regression and Variable Selection

Modified Cross-Validation for Penalized High-Dimensional Linear Regression Models

Yi Yu
&
Yang Feng
Pages 1009-1027 | Received 01 Sep 2012, Published online: 20 Oct 2014

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Onur Camli, Zeynep Kalaylioglu & Ashis SenGupta. (2023) Variable selection in linear-circular regression models. Journal of Applied Statistics 50:16, pages 3337-3361.
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Jiawei Zhang, Jie Ding & Yuhong Yang. (2023) Is a Classification Procedure Good Enough?—A Goodness-of-Fit Assessment Tool for Classification Learning. Journal of the American Statistical Association 118:542, pages 1115-1125.
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Zemin Zheng, Yang Li, Jie Wu & Yuchen Wang. (2022) Sequential Scaled Sparse Factor Regression. Journal of Business & Economic Statistics 40:2, pages 595-604.
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Ana María Estrada Gómez, Kamran Paynabar & Massimo Pacella. (2021) Functional directed graphical models and applications in root-cause analysis and diagnosis. Journal of Quality Technology 53:4, pages 421-437.
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Anna C. Wysocki & Mijke Rhemtulla. (2021) On Penalty Parameter Selection for Estimating Network Models. Multivariate Behavioral Research 56:2, pages 288-302.
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Abhirup Datta & Hui Zou. (2020) A Note on Cross-Validation for Lasso Under Measurement Errors. Technometrics 62:4, pages 549-556.
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Yang Li & Jun S. Liu. (2019) Robust Variable and Interaction Selection for Logistic Regression and General Index Models. Journal of the American Statistical Association 114:525, pages 271-286.
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Darren Homrighausen & Daniel J. McDonald. (2018) A study on tuning parameter selection for the high-dimensional lasso. Journal of Statistical Computation and Simulation 88:15, pages 2865-2892.
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Yoonsuh Jung. (2018) Multiple predicting K-fold cross-validation for model selection. Journal of Nonparametric Statistics 30:1, pages 197-215.
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Bingqing Lin, Zhen Pang, Jun Zhang & Cuiqing Chen. (2022) Fast feature selection via streamwise procedure for massive data. Brazilian Journal of Probability and Statistics 36:1.
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Zishu Zhan & Yuhong Yang. (2022) Profile electoral college cross-validation. Information Sciences 586, pages 24-40.
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Liye Lv, Xueguan Song & Wei Sun. (2020) Modify Leave-One-Out Cross Validation by Moving Validation Samples around Random Normal Distributions: Move-One-Away Cross Validation. Applied Sciences 10:7, pages 2448.
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Yang Feng, Tengfei Li & Zhiliang Ying. (2018) Likelihood adaptively modified penalties. Applied Stochastic Models in Business and Industry 35:2, pages 330-353.
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Tom Trigano & Yann Sepulcre. (2018) Data-driven parameter selection for activity estimation in nuclear spectroscopy. Signal Processing 151, pages 99-106.
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Qifan Song. (2018) An overview of reciprocal L 1 -regularization for high dimensional regression data . Wiley Interdisciplinary Reviews: Computational Statistics 10:1, pages e1416.
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Han Li, Colin O'hare & Farshid Vahid. (2016) A Flexible Functional Form Approach To Mortality Modeling: Do We Need Additional Cohort Dummies?. Journal of Forecasting 36:4, pages 357-367.
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Xiaoli Gao, S. Ejaz Ahmed & Yang Feng. (2017) Rejoinder to ‘Post‐selection shrinkage estimation for high‐dimensional data analysis’. Applied Stochastic Models in Business and Industry 33:2, pages 131-135.
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Cheryl J. Flynn, Clifford M. Hurvich & Jeffrey S. Simonoff. (2017) On the Sensitivity of the Lasso to the Number of Predictor Variables. Statistical Science 32:1.
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Yang Feng & Mengjia Yu. 2017. Big and Complex Data Analysis. Big and Complex Data Analysis 3 28 .
Han Li, Colin O'Hare & Farshid Vahid. (2015) A Flexible Functional Form Approach to Mortality Modeling. SSRN Electronic Journal.
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