8 citations · 14 across the 4 of their papers we have counts for
3 papers · 1 filter
Expectation-Propagation for Bayesian Empirical Likelihood Inference
Kenyon Ng, Weichang Yu, Howard D. Bondell
Bayesian inference typically relies on specifying a parametric model that approximates the data-generating process. However, misspecified models can yield poor convergence rates an…
Sparse high-dimensional linear regression with a partitioned empirical Bayes ECM algorithm
Alexander C. McLain, Anja Zgodic, Howard Bondell
Bayesian variable selection methods are powerful techniques for fitting and inferring on sparse high-dimensional linear regression models. However, many are computationally intensi…
Bayesian inference in high-dimensional linear models using an empirical correlation-adaptive prior
Chang Liu, Yue Yang, Howard Bondell +1
In the context of a high-dimensional linear regression model, we propose the use of an empirical correlation-adaptive prior that makes use of information in the observed predictor…