36 citations · 67 across the 5 of their papers we have counts for
5 papers · 1 filter
Superset model problem
Koji Miyawaki, Steven N. MacEachern
This paper focuses on the superset model problem that arises in the context of regression. To address this problem, we take the Bayesian approach to measure its uncertainty. An ill…
The Dependent Dirichlet Process and Related Models
Fernand A. Quintana, Peter Mueller, Alejandro Jara +1
Standard regression approaches assume that some finite number of the response distribution characteristics, such as location and scale, change as a (parametric or nonparametric) fu…
Economic variable selection
Steven N. MacEachern, Koji Miyawaki
Regression plays a key role in many research areas and its variable selection is a classic and major problem. This study emphasizes cost of predictors to be purchased for future us…
Regularization of Case-Specific Parameters for Robustness and Efficiency
Yoonkyung Lee, Steven N. MacEachern, Yoonsuh Jung
Regularization methods allow one to handle a variety of inferential problems where there are more covariates than cases. This allows one to consider a potentially enormous number o…
Restricting exchangeable nonparametric distributions
Sinead Williamson, Zoubin Ghahramani, Steven N. MacEachern +1
Distributions over exchangeable matrices with infinitely many columns, such as the Indian buffet process, are useful in constructing nonparametric latent variable models. However,…