Variable selection and estimation in generalized linear models with the seamless ${\it L}_{{\rm 0}}$ penalty

DOI10.1002/cjs.11165zbMath1348.62206OpenAlexW2011806156WikidataQ36693601 ScholiaQ36693601MaRDI QIDQ2856573

Zilin Li, Xihong Lin, Sijian Wang

Publication date: 29 October 2013

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.11165

zbMATH Keywords

consistencymodel selectionBICoracle propertycoordinate descent algorithmtuning parameter selectionpenalized likelihood methodsSELO penalty

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Statistical ranking and selection procedures (62F07)

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Cites Work

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• Nearly unbiased variable selection under minimax concave penalty
• The Adaptive Lasso and Its Oracle Properties
• Estimating the dimension of a model
• Heuristics of instability and stabilization in model selection
• Asymptotics for Lasso-type estimators.
• Nonconcave penalized likelihood with a diverging number of parameters.
• The risk inflation criterion for multiple regression
• On the adaptive elastic net with a diverging number of parameters
• Pathwise coordinate optimization
• On the ``degrees of freedom of the lasso
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Coordinate descent algorithms for lasso penalized regression
• Extended BIC for small-n-large-P sparse GLM
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Regularization Parameter Selections via Generalized Information Criterion
• Linear Model Selection by Cross-Validation
• Tuning parameter selectors for the smoothly clipped absolute deviation method
• Some Comments on C P
• A new look at the statistical model identification