We propose a Bayesian generalized low-rank regression model (GLRR) for the analysis of both high-dimensional responses and covariates. This development is motivated by performing searches for associations between genetic variants and brain imaging phenotypes. GLRR integrates a low rank matrix to...

The aim of this article is to develop a semiparametric model to describe the variability of the medial representation of subcortical structures, which belongs to a Riemannian manifold, and establish its association with covariates of interest, such as diagnostic status, age, and gender. We...