Consistency of Posterior Distributions for Heteroscedastic Nonparametric Regression Models

In this article, we consider Bayesian inferences for the heteroscedastic nonparametric regression models, when both the mean function and variance function are unknown. We demonstrated consistency of posterior distributions for this model using priors induced by B-splines expansion, treating both random and deterministic covariates in a uniform manner.