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On the robustness of the adaptive lasso to model misspecification

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Publication:2913861
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DOI10.1093/biomet/ass027zbMath1437.62547OpenAlexW2026159117WikidataQ34299477 ScholiaQ34299477MaRDI QIDQ2913861

Jason P. Fine, Yair Goldberg, Wen-Bin Lu

Publication date: 21 September 2012

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4188068


zbMATH Keywords

penalizationshrinkage estimationvariable selectionselection consistencyoracle propertymodel misspecificationleast false parameter


Mathematics Subject Classification ID

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


Related Items (7)

Exponentially tilted likelihood inference on growing dimensional unconditional moment models ⋮ Variable selection for categorical response: a comparative study ⋮ Double-slicing assisted sufficient dimension reduction for high-dimensional censored data ⋮ Oracle estimation of parametric transformation models ⋮ A fast adaptive Lasso for the cox regression via safe screening rules ⋮ An omnibus test for detection of subgroup treatment effects via data partitioning ⋮ Unnamed Item




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