Exact results on high-dimensional linear regression via statistical physics
Statistics Theory
2021-05-05 v4 Disordered Systems and Neural Networks
Statistics Theory
Abstract
It is clear that conventional statistical inference protocols need to be revised to deal correctly with the high-dimensional data that are now common. Most recent studies aimed at achieving this revision rely on powerful approximation techniques, that call for rigorous results against which they can be tested. In this context, the simplest case of high-dimensional linear regression has acquired significant new relevance and attention. In this paper we use the statistical physics perspective on inference to derive a number of new exact results for linear regression in the high-dimensional regime.
Cite
@article{arxiv.2009.13229,
title = {Exact results on high-dimensional linear regression via statistical physics},
author = {Alexander Mozeika and Mansoor Sheikh and Fabian Aguirre-Lopez and Fabrizio Antenucci and Anthony CC Coolen},
journal= {arXiv preprint arXiv:2009.13229},
year = {2021}
}
Comments
Most recent version accepted for publication in Physical Review E