62 citations · 153 across the 19 of their papers we have counts for
22 papers
Scalable and optimal Bayesian inference for sparse covariance matrices via screened beta-mixture prior
Kyoungjae Lee, Seongil Jo, Kyeongwon Lee +1
In this paper, we propose a scalable Bayesian method for sparse covariance matrix estimation by incorporating a continuous shrinkage prior with a screening procedure. In the first…
Estimation of World Seroprevalence of SARS-CoV-2 antibodies
Kwangmin Lee, Seongmin Kim, Seongil Jo +1
In this paper, we estimate the seroprevalence against COVID-19 by country and derive the seroprevalence over the world. To estimate seroprevalence, we use serological surveys (also…
Ordinary Differential Equation Models and their Computation Methods
Jaeyong Lee
In this article, I introduce the differential equation model and review their frequentist and Bayesian computation methods. A numerical example of the FitzHugh-Nagumo model is give…
Multivariate Lévy Adaptive B-Spline Regression
Sewon Park, Jaeyong Lee
We develop a fully Bayesian nonparametric regression model based on a Lévy process prior named MLABS (Multivariate Lévy Adaptive B-Spline regression) model, a multivariate version…
Post-Processed Posteriors for Sparse Covariances and Its Application to Global Minimum Variance Portfolio
Kwangmin Lee, Jaeyong Lee
We consider Bayesian inference of sparse covariance matrices and propose a post-processed posterior. This method consists of two steps. In the first step, posterior samples are obt…
Bayesian Nonparametric Classification for Incomplete Data With a High Missing Rate: an Application to Semiconductor Manufacturing Data
Sewon Park, Kyeongwon Lee, Da-Eun Jeong +2
During the semiconductor manufacturing process, predicting the yield of the semiconductor is an important problem. Early detection of defective product production in the manufactur…