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Bibliographic Details
Main Author: Brooks, Thomas G.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.05280
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author Brooks, Thomas G.
author_facet Brooks, Thomas G.
contents Efficient schemes for sampling from the eigenvalues of the Wishart distribution have recently been described for both the uncorrelated central case (where the covariance matrix is $\mathbf{I}$) and the spiked Wishart with a single spike (where the covariance matrix differs from $\mathbf{I}$ in a single entry on the diagonal). Here, we generalize these schemes to the spiked Wishart with an arbitrary number of spikes. This approach also applies to the spiked pseudo-Wishart distribution. We describe how to differentiate this procedure for the purposes of stochastic gradient descent, allowing the fitting of the eigenvalue distribution to some target distribution.
format Preprint
id arxiv_https___arxiv_org_abs_2410_05280
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Sampling Spiked Wishart Eigenvalues
Brooks, Thomas G.
Computation
Statistics Theory
60B20 (Primary)
Efficient schemes for sampling from the eigenvalues of the Wishart distribution have recently been described for both the uncorrelated central case (where the covariance matrix is $\mathbf{I}$) and the spiked Wishart with a single spike (where the covariance matrix differs from $\mathbf{I}$ in a single entry on the diagonal). Here, we generalize these schemes to the spiked Wishart with an arbitrary number of spikes. This approach also applies to the spiked pseudo-Wishart distribution. We describe how to differentiate this procedure for the purposes of stochastic gradient descent, allowing the fitting of the eigenvalue distribution to some target distribution.
title Sampling Spiked Wishart Eigenvalues
topic Computation
Statistics Theory
60B20 (Primary)
url https://arxiv.org/abs/2410.05280