• 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}
}
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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