The restricted consistency property of leave-nv-out cross-validation for high-dimensional variable selection

DOI10.5705/ss.202015.0394zbMath1422.62255arXiv1308.5390OpenAlexW2964259175MaRDI QIDQ5226652

Yi Yu, Yang Feng

Publication date: 1 August 2019

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1308.5390

zbMATH Keywords

variable selectiongeneralized linear modelsrestricted maximum likelihood estimatorsleave-\(n_v\)-out cross-validationrestricted model-selection consistency

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Statistical ranking and selection procedures (62F07)

Related Items (4)

High-dimensional regression with potential prior information on variable importance ⋮ A Tuning-free Robust and Efficient Approach to High-dimensional Regression ⋮ High-dimensional variable selection via low-dimensional adaptive learning ⋮ Targeted cross-validation

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