Lassoing Eigenvalues
Methodology
2018-05-23 v1
Abstract
The properties of penalized sample covariance matrices depend on the choice of the penalty function. In this paper, we introduce a class of non-smooth penalty functions for the sample covariance matrix, and demonstrate how this method results in a grouping of the estimated eigenvalues. We refer to this method as "lassoing eigenvalues" or as the "elasso".
Keywords
Cite
@article{arxiv.1805.08300,
title = {Lassoing Eigenvalues},
author = {David E. Tyler and Mengxi Yi},
journal= {arXiv preprint arXiv:1805.08300},
year = {2018}
}
Comments
18 pages, 6 figures