Principal Loading Analysis
Statistics Theory
2021-03-05 v2 Statistics Theory
Abstract
This paper proposes a tool for dimension reduction where the dimension of the original space is reduced: a Principal Loading Analysis (PLA). PLA is a tool to reduce dimensions by discarding variables. The intuition is that variables are dropped which distort the covariance matrix only by a little. Our method is introduced and an algorithm for conducting PLA is provided. Further, we give bounds for the noise arising in the sample case.
Keywords
Cite
@article{arxiv.2007.05215,
title = {Principal Loading Analysis},
author = {Jan O. Bauer and Bernhard Drabant},
journal= {arXiv preprint arXiv:2007.05215},
year = {2021}
}