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math.ST2025
Eigenstructure inference for high-dimensional covariance with generalized shrinkage inverse-Wishart prior
Seongmin Kim, Kwangmin Lee, Sewon Park +1
In multivariate statistics, estimating the covariance matrix is essential for understanding the interdependence among variables. In high-dimensional settings, where the number of c…
math.ST2025
Bayesian Analysis of Spiked Covariance Models: Correcting Eigenvalue Bias and Determining the Number of Spikes
Kwangmin Lee, Sewon Park, Seongmin Kim +1
We study Bayesian inference in the spiked covariance model, where a small number of spiked eigenvalues dominate the spectrum. Our goal is to infer the spiked eigenvalues, their cor…