Variable selection for binary spatial regression: Penalized quasi‐likelihood approach

DOI10.1111/biom.12525zbMath1390.62122OpenAlexW2341324644WikidataQ47712901 ScholiaQ47712901MaRDI QIDQ5355240

Chae Young Lim, Tapabrata Maiti, Abdhi Sarkar, Wenning Feng

Publication date: 7 September 2017

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/biom.12525

zbMATH Keywords

parameter estimationvariable selectionincreasing domain asymptoticsLassobinary responsespatial regressionSCADMM algorithmpenalized quasi-likelihood

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Point estimation (62F10)

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High dimensional classification for spatially dependent data with application to neuroimaging ⋮ Sparse spatially clustered coefficient model via adaptive regularization

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