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In arXiv:0911.2150, Rutger van Haasteren seeks to criticize the nestedsampling algorithm for Bayesian data analysis in general and its MultiNestimplementation in particular. He introduces a new method for evidenceevaluation based on the idea of Voronoi tessellation and requiring samples fromthe posterior distribution obtained through MCMC based methods. He compares itsaccuracy and efficiency with MultiNest, concluding that it outperformsMultiNest in several cases. This comparison is completely unfair since theproposed method can not perform the complete Bayesian data analysis includingposterior exploration and evidence evaluation on its own while MultiNest allowsone to perform Bayesian data analysis end to end. Furthermore, their criticismof nested sampling (and in turn MultiNest) is based on a few conceptualmisunderstandings of the algorithm. Here we seek to set the record straight.

Comment on "Bayesian evidence: can we beat MultiNest using traditional MCMC methods", by Rutger van Haasteren (arXiv:0911.2150)