Recovery of spectrum from estimated covariance matrices and statistical kernels for machine learning and big data
Probability
2018-04-26 v1 Statistics Theory
Statistics Theory
Abstract
In this paper we propose two schemes for the recovery of the spectrum of a covariance matrix from the empirical covariance matrix, in the case where the dimension of the matrix is a subunitary multiple of the number of observations. We test, compare and analyze these on simulated data and also on some data coming from the stock market.
Keywords
Cite
@article{arxiv.1804.09472,
title = {Recovery of spectrum from estimated covariance matrices and statistical kernels for machine learning and big data},
author = {Saba Amsalu and Juntao Duan and Heinrich Matzinger and Ionel Popescu},
journal= {arXiv preprint arXiv:1804.09472},
year = {2018}
}