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Science
Vol. 312 no. 5772 p. 367
DOI: 10.1126/science.1124180
  • Technical Comments

Response to Comment on "Phylogenetic MCMC Algorithms Are Misleading on Mixtures of Trees"

  1. Eric Vigoda2,*

+ Author Affiliations

  1. 1 Department of Statistics, University of California at Berkeley, Berkeley, CA 94720, USA.
  2. 2 College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA.
  1. ↵* To whom correspondence should be addressed. E-mail: mossel@stat.berkeley.edu; E-mail: vigoda@cc.gatech.edu

We presented a tree mixture in which Markov chain Monte Carlo (MCMC) methods have an exponentially slow convergence rate. We expect that many other mixture scenarios will show slow convergence. Ronquist et al. show that Metropolis-coupled MCMC (MC3) converges quickly on our mixture. However, they presented no theoretical or systematic experimental evidence determining the type of mixtures where MC3 or other methods are efficient.

  • Received for publication 5 January 2006.
  • Accepted for publication 23 March 2006.
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