Speaker
Charbel Abi Younes
(University of Washington)
Description
We introduce a new approach for estimating the asymptotic spectral distribution (ASD) of a random matrix using a single, sufficiently high-dimensional sample, without computing the full spectrum. The method builds on the Lanczos algorithm, together with asymptotic analysis and perturbation theory for orthogonal polynomials, and enables efficient and accurate estimation of the ASD. We illustrate the approach through an application to spectral density estimation in spiked covariance models.
Authors
Charbel Abi Younes
(University of Washington)
Dr
Thomas Trogdon
(University of Washington)
Dr
Xiucai Ding
(UC Davis)