2 papers
stat.ME2019
Bayesian Variable Selection for Gaussian copula regression models
Angelos Alexopoulos, Leonardo Bottolo
We develop a novel Bayesian method to select important predictors in regression models with multiple responses of diverse types. A sparse Gaussian copula regression model is used t…
stat.AP2018
A global-local approach for detecting hotspots in multiple-response regression
Hélène Ruffieux, Anthony C. Davison, Jörg Hager +4
We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, i.e., predictors associated…