On choosing the centering distribution in Dirichlet process mixture models

We present two results that pertain to the choosing of the centering distribution in a Bayesian setup with a Dirichlet process mixture prior based on Gaussian kernels. Our results indicate that for such kernels, one can choose the centering measure for the Dirichlet process mixture model exactly as one would in the analogous simpler Dirichlet process model.