Paths Following Algorithm for Penalized Logistic Regression Using SCAD and MCP

DOI10.1080/03610918.2012.725146zbMath1291.62128OpenAlexW2090718738WikidataQ107392657 ScholiaQ107392657MaRDI QIDQ5415904

Cun-Hui Zhang, Wenhua Jiang

Publication date: 19 May 2014

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2012.725146

zbMATH Keywords

variable selectionpenalized likelihoodMCPSCADconcave penalization

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (2)

A novel variational Bayesian method for variable selection in logistic regression models ⋮ Coordinate majorization descent algorithm for nonconvex penalized regression

Cites Work

• Nearly unbiased variable selection under minimax concave penalty
• One-step sparse estimates in nonconcave penalized likelihood models
• Nonconcave penalized likelihood with a diverging number of parameters.
• Least angle regression. (With discussion)
• Pathwise coordinate optimization
• Variable selection using MM algorithms
• Piecewise linear regularized solution paths
• Scaled sparse linear regression
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

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