6 citations · 13 across the 10 of their papers we have counts for
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Bayesian inference on hierarchical nonlocal priors in generalized linear models
Xuan Cao, Kyoungjae Lee
Variable selection methods with nonlocal priors have been widely studied in linear regression models, and their theoretical and empirical performances have been reported. However,…
Consistent and scalable Bayesian joint variable and graph selection for disease diagnosis leveraging functional brain network
Xuan Cao, Kyoungjae Lee
We consider the joint inference of regression coefficients and the inverse covariance matrix for covariates in high-dimensional probit regression, where the predictors are both rel…
Bayesian joint inference for multiple directed acyclic graphs
Kyoungjae Lee, Xuan Cao
In many applications, data often arise from multiple groups that may share similar characteristics. A joint estimation method that models several groups simultaneously can be more…
Bayesian Group Selection in Logistic Regression with Application to MRI Data Analysis
Kyoungjae Lee, Xuan Cao
We consider Bayesian logistic regression models with group-structured covariates. In high-dimensional settings, it is often assumed that only small portion of groups are significan…
A permutation-based Bayesian approach for inverse covariance estimation
Xuan Cao, Shaojun Zhang
Covariance estimation and selection for multivariate datasets in a high-dimensional regime is a fundamental problem in modern statistics. Gaussian graphical models are a popular cl…
Posterior Graph Selection and Estimation Consistency for High-dimensional Bayesian DAG Models
Xuan Cao, Kshitij Khare, Malay Ghosh
Covariance estimation and selection for high-dimensional multivariate datasets is a fundamental problem in modern statistics. Gaussian directed acyclic graph (DAG) models are a pop…