Bayesian inverse-Wishart inference for spiked covariance matrices is extended with eigenvalue bias corrections and a BIC-based spike count that is consistent when p exceeds n.
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Bayesian Analysis of Spiked Covariance Models: Correcting Eigenvalue Bias and Determining the Number of Spikes
Bayesian inverse-Wishart inference for spiked covariance matrices is extended with eigenvalue bias corrections and a BIC-based spike count that is consistent when p exceeds n.