  In arXiv:0911.2150, Rutger van Haasteren seeks to criticize the nested
sampling algorithm for Bayesian data analysis in general and its MultiNest
implementation in particular. He introduces a new method for evidence
evaluation based on the idea of Voronoi tessellation and requiring samples from
the posterior distribution obtained through MCMC based methods. He compares its
accuracy and efficiency with MultiNest, concluding that it outperforms
MultiNest in several cases. This comparison is completely unfair since the
proposed method can not perform the complete Bayesian data analysis including
posterior exploration and evidence evaluation on its own while MultiNest allows
one to perform Bayesian data analysis end to end. Furthermore, their criticism
of nested sampling (and in turn MultiNest) is based on a few conceptual
misunderstandings of the algorithm. Here we seek to set the record straight.
