A general framework for approximate sampling with an application to generating points on the boundary of bounded convex regions

H. E. Romeijn

Statistica Neerlandica, 1998, vol. 52, issue 1, 42-59

Abstract: We consider the problem of generating a sample of points according to some given probability distribution over some region. We give a general framework for constructing approximate sampling algorithms based on the theory of Markov chains. In particular, we show how it can be proven that a Markov chain has a limiting distribution. We apply these results to prove convergence for a class of so‐called Shake‐and‐Bake algorithms, which can be used to approximate any absolutely continuous distribution over the boundary of a full‐dimensional convex body.

Date: 1998
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