EEBoost: A General Method for Prediction and Variable Selection Based on Estimating Equations

DOI10.1198/JASA.2011.TM10098zbMath1396.62036OpenAlexW2046124401MaRDI QIDQ5256421

Julian Wolfson

Publication date: 17 June 2015

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/jasa.2011.tm10098

zbMATH Keywords

predictionmodel selectionboostingprojected likelihood

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10)

Related Items (2)

De-noising boosting methods for variable selection and estimation subject to error-prone variables ⋮ EEBoost

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