A note on the variance in principal component regression
Methodology
2023-06-30 v3 Statistics Theory
Statistics Theory
Abstract
Principal component regression results in lack of fit when important dimensions are omitted, which cannot be assessed from the eigenvalues. I show that the PC-regression estimator can also suffer from increased variance relative to ordinary least squares in such cases.
Cite
@article{arxiv.2301.01543,
title = {A note on the variance in principal component regression},
author = {Bert van der Veen},
journal= {arXiv preprint arXiv:2301.01543},
year = {2023}
}
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6 pages, 0 figures