Nested Sampling is a numerical algorithm for approximate Bayesian inference. It generates samples from the posterior distribution but its main purpose is to estimate the evidence P(M|D) of the model conditioned on the observed data. More information on Nested Sampling is available at http://en.wikipedia.org/wiki/Nested_sampling_algorithm. The original code can be found at http://www.inference.phy.cam.ac.uk/bayesys/sivia/ along with documentation at http://www.inference.phy.cam.ac.uk/bayesys/. An example program called lighthouse.hs is included. So far, only the simple demonstration file called mininest.c has been ported. There is a more sophisticated C library available at http://www.inference.phy.cam.ac.uk/bayesys/nest/nest.tar.gz but it has not been ported to Haskell yet.