Dimension reduction and variable selection in case control studies via regularized likelihood optimization

DOI10.1214/09-EJS537zbMath1326.62161arXiv0905.2171MaRDI QIDQ1952024

Florentina Bunea, Adrian Barbu

Publication date: 27 May 2013

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

Full work available at URL: https://arxiv.org/abs/0905.2171

zbMATH Keywords

regularizationmodel selectiondimension reductionlogistic regressioncase-control studiesbisection methodLassoretrospective samplingprospective sampling

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Design of statistical experiments (62K99) Generalized linear models (logistic models) (62J12)

Related Items

An iterative algorithm for fitting nonconvex penalized generalized linear models with grouped predictors, SPADES and mixture models, Global and local two-sample tests via regression, Tight conditions for consistency of variable selection in the context of high dimensionality

Uses Software

• hgam

Cites Work

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