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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…
math.ST2025
Conditional Dirichlet Processes and Functional Condition Models
Jaeyong Lee, Kwangmin Lee, Jaegui Lee +1
In this paper, we study the conditional Dirichlet process (cDP) when a functional of a random distribution is specified. Specifically, we apply the cDP to the functional condition…