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Error bounds for Approximations of Markov chains used in Bayesian Sampling

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arxiv 1711.05382 v2 pith:2F3QOFYX submitted 2017-11-15 math.PR

James E. Johndrow , Jonathan C. Mattingly This is my paper · ORCID
classification math.PR
keywords approximationsbayesiankernelsmarkovresultsappliedboundschains
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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.

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