From owner-svn-ports-all@FreeBSD.ORG Fri Nov 23 02:32:01 2012 Return-Path: Delivered-To: svn-ports-all@freebsd.org Received: from mx1.freebsd.org (mx1.freebsd.org [69.147.83.52]) by hub.freebsd.org (Postfix) with ESMTP id A6E7580C; Fri, 23 Nov 2012 02:32:01 +0000 (UTC) (envelope-from tota@FreeBSD.org) Received: from svn.freebsd.org (svn.freebsd.org [IPv6:2001:1900:2254:2068::e6a:0]) by mx1.freebsd.org (Postfix) with ESMTP id 8D8D98FC13; Fri, 23 Nov 2012 02:32:01 +0000 (UTC) Received: from svn.freebsd.org (localhost [127.0.0.1]) by svn.freebsd.org (8.14.5/8.14.5) with ESMTP id qAN2W1aV018638; Fri, 23 Nov 2012 02:32:01 GMT (envelope-from tota@svn.freebsd.org) Received: (from tota@localhost) by svn.freebsd.org (8.14.5/8.14.5/Submit) id qAN2W13I018634; Fri, 23 Nov 2012 02:32:01 GMT (envelope-from tota@svn.freebsd.org) Message-Id: <201211230232.qAN2W13I018634@svn.freebsd.org> From: TAKATSU Tomonari Date: Fri, 23 Nov 2012 02:32:01 +0000 (UTC) To: ports-committers@freebsd.org, svn-ports-all@freebsd.org, svn-ports-head@freebsd.org Subject: svn commit: r307669 - in head/math: . R-cran-LearnBayes X-SVN-Group: ports-head MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit X-BeenThere: svn-ports-all@freebsd.org X-Mailman-Version: 2.1.14 Precedence: list List-Id: SVN commit messages for the ports tree List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Fri, 23 Nov 2012 02:32:01 -0000 Author: tota Date: Fri Nov 23 02:32:01 2012 New Revision: 307669 URL: http://svnweb.freebsd.org/changeset/ports/307669 Log: - Add a new port: math/R-cran-LearnBayes LearnBayes contains a collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling. WWW: http://cran.r-project.org/web/packages/LearnBayes/ Feature safe: yes Added: head/math/R-cran-LearnBayes/ head/math/R-cran-LearnBayes/Makefile (contents, props changed) head/math/R-cran-LearnBayes/distinfo (contents, props changed) head/math/R-cran-LearnBayes/pkg-descr (contents, props changed) Modified: head/math/Makefile Modified: head/math/Makefile ============================================================================== --- head/math/Makefile Fri Nov 23 02:27:09 2012 (r307668) +++ head/math/Makefile Fri Nov 23 02:32:01 2012 (r307669) @@ -8,6 +8,7 @@ SUBDIR += R SUBDIR += R-cran-Formula SUBDIR += R-cran-KFAS + SUBDIR += R-cran-LearnBayes SUBDIR += R-cran-MCMCpack SUBDIR += R-cran-RSvgDevice SUBDIR += R-cran-SuppDists Added: head/math/R-cran-LearnBayes/Makefile ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/R-cran-LearnBayes/Makefile Fri Nov 23 02:32:01 2012 (r307669) @@ -0,0 +1,18 @@ +# Created by: TAKATSU Tomonari +# $FreeBSD$ + +PORTNAME= LearnBayes +PORTVERSION= 2.12 +CATEGORIES= math +DISTNAME= ${PORTNAME}_${PORTVERSION} + +MAINTAINER= tota@FreeBSD.org +COMMENT= Functions for Learning Bayesian Inference + +LICENSE= GPLv2 GPLv3 +LICENSE_COMB= dual + +USE_R_MOD= yes +R_MOD_AUTOPLIST= yes + +.include Added: head/math/R-cran-LearnBayes/distinfo ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/R-cran-LearnBayes/distinfo Fri Nov 23 02:32:01 2012 (r307669) @@ -0,0 +1,2 @@ +SHA256 (LearnBayes_2.12.tar.gz) = 5559d5fcceda7b695a62b88b8288a15367ea176b6d8769a8f811f0e9b8a3d37a +SIZE (LearnBayes_2.12.tar.gz) = 88819 Added: head/math/R-cran-LearnBayes/pkg-descr ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/R-cran-LearnBayes/pkg-descr Fri Nov 23 02:32:01 2012 (r307669) @@ -0,0 +1,9 @@ +LearnBayes contains a collection of functions helpful in learning +the basic tenets of Bayesian statistical inference. It contains +functions for summarizing basic one and two parameter posterior +distributions and predictive distributions. It contains MCMC +algorithms for summarizing posterior distributions defined by the +user. It also contains functions for regression models, hierarchical +models, Bayesian tests, and illustrations of Gibbs sampling. + +WWW: http://cran.r-project.org/web/packages/LearnBayes/