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Outlier-robustness in adaptations to the lasso
2018Model selection in regression techniques has risen to the forefront in recent statistical applications. Regularization methods, and the lasso especially, have seen increasing attention in the past decade, with a variety of adaptations developed to enhance the robustness of the model selection capabilities of these techniques.
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CAViaR Model Selection via Adaptive Lasso
Journal of Time Series AnalysisABSTRACT The estimation and model selection of the conditional autoregressive value at risk (CAViaR) model may be computationally intensive and even impractical when the true order of the quantile autoregressive components or the dimension of the other regressors are high.
Zongwu Cai, Ying Fang, Dingshi Tian
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Asymptotic theory of the adaptive Sparse Group Lasso
Annals of the Institute of Statistical Mathematics, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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The Selectively Adaptive Lasso.
CoRR, 2022Alejandro Schuler, Mark J. van der Laan
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An Adaptive Sieving Strategy for the Complex Lasso Problem
2023 6th International Conference on Data Science and Information Technology (DSIT), 2023Xiaoning Bai, Yuge Ye, Qingna Li
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The Adaptive Lasso and Its Oracle Properties
Journal of the American Statistical Association, 2006Hui Zou
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