Error bounds for Approximations of Markov chains used in Bayesian Sampling
/ Authors
/ Abstract
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.
Journal: arXiv: Probability