11 citations · 17 across the 6 of their papers we have counts for
6 papers
Empirical Bayes large-scale multiple testing for high-dimensional binary outcome data
Yu-Chien Bo Ning
This paper explores the multiple testing problem for sparse high-dimensional data with binary outcomes. We propose novel empirical Bayes multiple testing procedures based on a spik…
Bayesian Multiscale Analysis of the Cox Model
Bo Y. -C. Ning, Ismaël Castillo
Piecewise constant priors are routinely used in the Bayesian Cox proportional hazards model for survival analysis. Despite its popularity, large sample properties of this Bayesian…
Empirical priors and coverage of posterior credible sets in a sparse normal mean model
Ryan Martin, Bo Ning
Bayesian methods provide a natural means for uncertainty quantification, that is, credible sets can be easily obtained from the posterior distribution. But is this uncertainty quan…
Bayesian Linear Regression for Multivariate Responses Under Group Sparsity
Bo Ning, Seonghyun Jeong, Subhashis Ghosal
We study frequentist properties of a Bayesian high-dimensional multivariate linear regression model with correlated responses. The predictors are separated into many groups and the…
Bayesian method for causal inference in spatially-correlated multivariate time series
Bo Ning, Subhashis Ghosal, Jewell Thomas
Measuring the causal impact of an advertising campaign on sales is an essential task for advertising companies. Challenges arise when companies run advertising campaigns in multipl…
Bayesian inference for generalized extreme value distribution with Gaussian copula dependence
Bo Ning, Peter Bloomfield
Dependent generalized extreme value (dGEV) models have attracted much attention due to the dependency structure that often appears in real datasets. To construct a dGEV model, a na…