Communications in Applied Mathematics and Computational Science

Ensemble samplers with affine invariance

Jonathan Goodman and Jonathan Weare

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We propose a family of Markov chain Monte Carlo methods whose performance is unaffected by affine tranformations of space. These algorithms are easy to construct and require little or no additional computational overhead. They should be particularly useful for sampling badly scaled distributions. Computational tests show that the affine invariant methods can be significantly faster than standard MCMC methods on highly skewed distributions.

Article information

Commun. Appl. Math. Comput. Sci., Volume 5, Number 1 (2010), 65-80.

Received: 6 November 2009
Accepted: 29 November 2009
First available in Project Euclid: 20 December 2017

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Zentralblatt MATH identifier

Primary: 65C05: Monte Carlo methods

Markov chain Monte Carlo affine invariance ensemble samplers


Goodman, Jonathan; Weare, Jonathan. Ensemble samplers with affine invariance. Commun. Appl. Math. Comput. Sci. 5 (2010), no. 1, 65--80. doi:10.2140/camcos.2010.5.65.

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