Flexible variable selection for recovering sparsity in nonadditive nonparametric models

DOI10.1111/BIOM.12518zbMath1390.62253arXiv1206.2696OpenAlexW2257061815WikidataQ45031595 ScholiaQ45031595MaRDI QIDQ5355238

Partrick Schaumont, Inyoung Kim, Zaili Fang

Publication date: 7 September 2017

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1206.2696

zbMATH Keywords

variable selectionLassosparsistencykernel learningnonnegative garrotenonparametric modelsmultivariate smoothing function

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

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