Geodesic
Variable selection using stepdown procedures in high-dimensional linear models
Konrad Furmańczyk1
1 Department of Applied Mathematics Warsaw University of Life Sciences (SGGW) Nowoursynowska 159 02-776 Warszawa, Poland
Applicationes Mathematicae, Tome 43 (2016) no. 2, pp. 157-172 Cet article a éte moissonné depuis la source Institute of Mathematics Polish Academy of Sciences

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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.
DOI : 10.4064/am2286-6-2016
Keywords: study variable selection problem high dimensional linear models gaussian non gaussian errors based ridge estimation hlmann considering problem variable selection problem multiple hypotheses testing under technical assumptions prove stepdown procedures consistent variable selection high dimensional linear model

Konrad Furmańczyk 1

1 Department of Applied Mathematics Warsaw University of Life Sciences (SGGW) Nowoursynowska 159 02-776 Warszawa, Poland 
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Konrad Furmańczyk. Variable selection using stepdown procedures in high-dimensional linear models. Applicationes Mathematicae, Tome 43 (2016) no. 2, pp. 157-172. doi: 10.4064/am2286-6-2016

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