7 citations · 8 across the 6 of their papers we have counts for
7 papers
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…
Identifiability of the Multinomial Processing Tree-IRT model for the Philadelphia Naming Test
Andrew J. Womack, Daniel Taylor-Rodriguez, Gerasimos Fergadiotis +1
Naming tests represent an essential tool in gauging the severity of aphasia and monitoring the trajectory of recovery for individuals afflicted with this debilitating condition. In…
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…
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…
The matryoshka doll prior: principled multiplicity correction in Bayesian model comparison
Andrew J Womack, Daniel Taylor-Rodriguez, Claudio Fuentes
This paper introduces a general and principled construction of model space priors with a focus on regression problems. The proposed formulation regards each model as a `local` null…
Intrinsic Bayesian Analysis for Occupancy Models
Daniel Taylor-Rodriguez, Andrew Womack, Claudio Fuentes +1
Occupancy models are typically used to determine the probability of a species being present at a given site while accounting for imperfect detection. The survey data underlying the…
Bayesian Variable Selection on Model Spaces Constrained by Heredity Conditions
Daniel Taylor-Rodriguez, Andrew Womack, Nikolay Bliznyuk
This paper investigates Bayesian variable selection when there is a hierarchical dependence structure on the inclusion of predictors in the model. In particular, we study the type…