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OCaml Markov Chain Monte Carlo
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farr/mcmc-ocaml
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SUMMARY This library implements a general MCMC sampler and associated libraries, including * The methods described in Farr and Mandel (2011) (http://arxiv.org/abs/1104.0984 ) for interpolating jump proposals in a reversible jump MCMC. * The evidence calculation methods from Weinberg's paper on Computing the Bayesian Factor from a Markov chain Monte Carlo Simulation of the Posterior Distribution (http://arxiv.org/abs/0911.1777 ). Also in the library is a simple nested-sampling implementation (see Skilling, J. Nested Sampling. AIP Conference Proceedings, vol. 735, pp. 395--405, 2004.). BUILDING * To build the library, use ocamlbuild: ocamlbuild mcmc.cma mcmc.cmxa * To build the code documentation: ocamlbuild mcmc.docdir/index.html * To build all of the above at once, use ocamlbuild all.otarget * To build the test suite, you will require oUnit (http://ounit.forge.ocamlcore.org/ ). Edit the myocamlbuild.ml file to point to your oUnit installation, and then issue ocamlbuild run_tests.{native,byte} If you encounter compilation errors, then you may have to modify the definition of the cmp_float function to: (* Compare floats up to a given relative error *) let cmp_float ?(epsabs = eps) ?(epsrel = eps) a b = let dx = abs_float (a -. b) and avg = 0.5*.((abs_float a) +. (abs_float b)) in dx <= epsabs +. epsrel*.avg * Various useful example programs can be found in the bin/ subdirectory; you can build them with ocamlbuild <program_name>.{native,byte} * To clean the code, issue the command ocamlbuild -clean LICENSE This library is released under the GPL version 3; see the LICENSE file for more information.
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