Smooth Scalar-on-Image Regression via Spatial Bayesian Variable Selection
Smooth Scalar-on-Image Regression via Spatial Bayesian Variable Selection
AbstractWe develop scalar-on-image regression models when images are registered multidimensional manifolds. We propose a fast and scalable Bayes' inferential procedure to estimate the image coefficient. The central idea is the combination of an Ising prior distribution, which controls a latent binary indicator map, and an intrinsic Gaussian Markov random field, …