arXiv · 1708.03551
On the overestimation of the largest eigenvalue of a covariance matrix
Abstract
In this paper, we use a new approach to prove that the largest eigenvalue of the sample covariance matrix of a normally distributed vector is bigger than the true largest eigenvalue with probability 1 when the dimension is infinite. We prove a similar result for the smallest eigenvalue.
Explore related subjects
Keep this discovery
Soufiane Hayou. 2017-08-11. On the overestimation of the largest eigenvalue of a covariance matrix. https://arxiv.org/abs/1708.03551
Cite the original work for its findings. Save a collection to share your selection of sources.