Ensemble samplers with affine invariance

Jonathan Goodman, Jonathan Weare

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)65-80
Number of pages16
JournalCommunications in Applied Mathematics and Computational Science
Issue number1
StatePublished - 2010


  • Affine invariance
  • Ensemble samplers
  • Markov chain Monte Carlo

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Theory and Mathematics
  • Applied Mathematics


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