1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.ST2026
Bayesian Multiplicity Correction in the Probabilistic Forward Stepwise Framework
Andrew Womack, Daniel Taylor-Rodriguez
We develop a natural Bayesian multiplicity-correcting prior distribution within the probabilistic forward stepwise representation of model space priors for regression problems. The…
math.ST2019
Revisiting High Dimensional Bayesian Model Selection for Gaussian Regression
Zikun Yang, Andrew Womack
Model selection for regression problems with an increasing number of covariates continues to be an important problem both theoretically and in applications. Model selection consist…
math.ST2019★ 1 cited
Heavy Tailed Horseshoe Priors
Andrew Womack, Zikun Yang
Locally adaptive shrinkage in the Bayesian framework is achieved through the use of local-global prior distributions that model both the global level of sparsity as well as individ…