• Corpus ID: 4565761

# Asymptotic normality and analysis of variance of log-likelihood ratios in spiked random matrix models

@article{Banerjee2018AsymptoticNA,
title={Asymptotic normality and analysis of variance of log-likelihood ratios in spiked random matrix models},
author={Debapratim Banerjee and Zongming Ma},
journal={ArXiv},
year={2018},
volume={abs/1804.00567}
}
• Published 2 April 2018
• Mathematics
• ArXiv
The present manuscript studies signal detection by likelihood ratio tests in a number of spiked random matrix models, including but not limited to Gaussian mixtures and spiked Wishart covariance matrices. We work directly with multi-spiked cases in these models and with flexible priors on the signal component that allow dependence across spikes. We derive asymptotic normality for the log-likelihood ratios when the signal-to- noise ratios are below certain thresholds. In addition, we show that…
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