3 papers
stat.ME2025
Bayesian Bootstrap based Gaussian Copula Model for Mixed Data with High Missing Rates
Seongmin Kim, Jeunghun Oh, Hungkuk Ko +2
Missing data is a common issue in various fields such as medicine, social sciences, and natural sciences, and it poses significant challenges for accurate statistical analysis. Alt…
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.ST2024
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…