Error bounds for Approximations of Markov chains used in Bayesian
We give a number of results on approximations of Markov kernels in total
variation and Wasserstein norms weighted by a Lyapunov function. The results
are applied to examples from Bayesian statistics where approximations to
transition kernels are made to reduce computational costs.