nilsbecker / mcmc-ocaml Goto Github PK

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.