Variable selection using stepdown procedures in high-dimensional linear models

Volume 43 / 2016

Konrad Furmańczyk Applicationes Mathematicae 43 (2016), 157-172 MSC: Primary 62J15, 62F03; Secondary 62J05. DOI: 10.4064/am2286-6-2016 Published online: 25 August 2016

Abstract

We study the variable selection problem in high-dimensional linear models with Gaussian and non-Gaussian errors. Based on Ridge estimation, as in Bühlmann (2013) we are considering the problem of variable selection as the problem of multiple hypotheses testing. Under some technical assumptions we prove that stepdown procedures are consistent for variable selection in a high-dimensional linear model.

Authors

  • Konrad FurmańczykDepartment of Applied Mathematics
    Warsaw University of Life Sciences (SGGW)
    Nowoursynowska 159
    02-776 Warszawa, Poland
    e-mail

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