NestedSampling: A port of John Skilling's nested sampling C code to Haskell.
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.
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|Versions [faq]||0.1.1, 0.1.2, 0.1.3, 0.1.4|
|Dependencies||base (==4.*), random, vector [details]|
|Copyright||(C) Sivia, Skilling 2006, Trotts 2011|
|Source repo||head: git clone git://github.com/ijt/haskell_nested_sampling.git|
|Uploaded||by IssacTrotts at 2011-09-22T07:24:27Z|
|Downloads||3214 total (2 in the last 30 days)|
|Rating||(no votes yet) [estimated by Bayesian average]|
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