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We give a number of results on approximations of Markov kernels in totalvariation and Wasserstein norms weighted by a Lyapunov function. The resultsare applied to examples from Bayesian statistics where approximations totransition kernels are made to reduce computational costs.

Error bounds for Approximations of Markov chains used in Bayesian Sampling