J. Ouyang

Scalable network-driven variable selection in Bayesian linear regression

This work develops a generalized-distribution-based Bayesian approach for consistent network-guided variable selection in high-dimensional linear regression and incorporates hierarchical spike-and-slab priors on the regression coefficients and the elements of the inverse covariance matrix.