Bayesian linear regression with sparse priors

Ismaël Castillo, Johannes Schmidt-Hieber, Aad van der Vaart

We study full Bayesian procedures for high-dimensional linear regression under sparsity constraints. The prior is a mixture of point masses at zero and continuous distributions. Un…