A nonparametric dependent process for Bayesian regression

This article investigates the problem of Bayesian nonparametric regression. The proposed model is based on a recently introduced random distribution function, which is based on a decreasing set of weights. The approach is surprisingly of a much simpler form than alternative models described in the literature. A Gibbs sampler algorithm is provided for posterior analysis.