Large numbers of explanatory variables: a probabilistic assessment.

Published in: Proceedings. Mathematical, physical, and engineering sciences (2018)

Recently, Cox and Battey (2017 Proc. Natl Acad. Sci. USA114, 8592-8595 (doi:10.1073/pnas.1703764114)) outlined a procedure for regression analysis when there are a small number of study individuals and a large number of potential explanatory variables, but relatively few of the latter have a real effect. The present paper reports more formal statistical properties. The results are intended primarily to guide the choice of key tuning parameters.

Keyphrases

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