Bayesian Nonparametric Spatial Modeling With Dirichlet Process Mixing

Abstract
Customary modeling for continuous point-referenced data assumes a Gaussian process that is often taken to be stationary. When such models are fitted within a Bayesian framework, the unknown paramet...

This publication has 2 references indexed in Scilit: