Optimal Bayesian estimation in random covariate design with a rescaled Gaussian process prior

In Bayesian nonparametric models, Gaussian processes provide a popular prior choice for regression function estimation. Existing literature on the theoretical investigation of the resulting posterior distribution almost exclusively assume a fixed design for covariates. The only random design result we are aware of (van der Vaart and van Zanten, 2011… (More)