From mboxrd@z Thu Jan 1 00:00:00 1970 Received: from mail3-relais-sop.national.inria.fr (mail3-relais-sop.national.inria.fr [192.134.164.104]) by walapai.inria.fr (8.13.6/8.13.6) with ESMTP id p370hHoN022818 for ; Thu, 7 Apr 2011 02:43:17 +0200 X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AogAAPgHnU2BaRBgkWdsb2JhbACYdI0NFAEBAQEJCwsHFAUguyWIbYVsBA X-IronPort-AV: E=Sophos;i="4.63,313,1299452400"; d="scan'208";a="80349812" Received: from mailp6.ci.northwestern.edu ([129.105.16.96]) by mail3-smtp-sop.national.inria.fr with ESMTP; 07 Apr 2011 02:43:11 +0200 Received: from eamu.home (pool-173-66-20-171.washdc.fios.verizon.net [173.66.20.171]) (using TLSv1 with cipher AES256-SHA (256/256 bits)) (No client certificate requested) by mailp6.ci.northwestern.edu (Postfix) with ESMTP id BDC1376DFB; Wed, 6 Apr 2011 19:43:09 -0500 (CDT) Message-ID: <4D9D089D.1000008@northwestern.edu> Date: Wed, 06 Apr 2011 20:43:09 -0400 From: Will M Farr User-Agent: Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.6; en-US; rv:1.9.2.15) Gecko/20110303 Thunderbird/3.1.9 MIME-Version: 1.0 To: caml-list@inria.fr CC: Ilya Mandel Content-Type: text/plain; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: 7bit Subject: [Caml-list] ANN: mcmc-ocaml: A Library for Markov-Chain Monte Carlo Computations in OCaml Hello all, I'd like to announce mcmc-ocaml, a library for Markov-chain Monte Carlo computations in OCaml. You can obtain the library from github at https://github.com/farr/mcmc-ocaml It is released under the GPL, version 3.0. For more information on MCMC, see http://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo . Some highlights of the mcmc-ocaml library: * mcmc-ocaml provides code to perform MCMC analysis in arbitrary parameter spaces. Parameter values need not be numerical, but can instead be any OCaml value: algebraic data types, classes, etc. * mcmc-ocaml provides useful higher-order functions to combine multiple jump proposals with arbitrary weights into a single proposal for Metropolis-Hastings sampling, making it easy to have many special jump proposals tuned to your specific parameter space structure. * mcmc-ocaml provides code to read and write MCMC samples from/to files; this can be combined with the library of statistical functions or user-written code to perform post-processing of MCMC output either in a stand-alone program or from the REPL. * mcmc-ocaml provides many utility functions for performing model selection via Reversible-Jump MCMC, either between two models or among a larger set of models. This includes an implementation of the method described in http://arxiv.org/abs/1104.0984 for facilitating inter-model jumps by interpolating posteriors using single model parameter samples. * mcmc-ocaml provides several different algorithms for computing the Bayesian evidence for a model using MCMC samples from its posterior distribution, including the "direct integration" algorithms described in http://arxiv.org/abs/0911.1777 . * mcmc-ocaml comes with complete ocamldoc documentation for its functions and types. mcmc-ocaml is extensively tested, and has been used to constrain the mass distribution of stellar-mass black holes in our galaxy (http://arxiv.org/abs/1011.1459 ---including the 10-way RJMCMC comparisons among the models in that paper), among other research projects. Please direct bug reports, feature requests, and comments to this address (w-farr@northwestern.edu). Thanks, Will