The Short-Cut Metropolis Method
Statistics Theory
2007-06-13 v1 Statistics Theory
Abstract
I show how one can modify the random-walk Metropolis MCMC method in such a way that a sequence of modified Metropolis updates takes little computation time when the rejection rate is outside a desired interval. This allows one to effectively adapt the scale of the Metropolis proposal distribution, by performing several such "short-cut" Metropolis sequences with varying proposal stepsizes. Unlike other adaptive Metropolis schemes, this method converges to the correct distribution in the same fashion as the standard Metropolis method.
Cite
@article{arxiv.math/0508060,
title = {The Short-Cut Metropolis Method},
author = {Radford M. Neal},
journal= {arXiv preprint arXiv:math/0508060},
year = {2007}
}