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- Add a new port: math/R-cran-MCMCpack

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This package contains functions to perform Bayesian inference using
  posterior simulation for a number of statistical models. Most
  simulation is done in compiled C++ written in the Scythe Statistical
  Library Version 1.0.3. All models return coda mcmc objects that can
  then be summarized using the coda package. MCMCpack also contains
  some useful utility functions, including some additional density
  functions and pseudo-random number generators for statistical
  distributions, a general purpose Metropolis sampling algorithm, and
  tools for visualization.

  WWW: http://cran.r-project.org/web/packages/MCMCpack/

Feature safe:	yes
This commit is contained in:
TAKATSU Tomonari 2012-11-18 04:34:53 +00:00
parent dbfc86e017
commit f2d232e386
Notes: svn2git 2021-03-31 03:12:20 +00:00 
svn path=/head/; revision=307527
4 changed files with 35 additions and 0 deletions
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1
math/Makefile
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@ -8,6 +8,7 @@
SUBDIR += R
SUBDIR += R-cran-Formula
SUBDIR += R-cran-KFAS
SUBDIR += R-cran-MCMCpack
SUBDIR += R-cran-RSvgDevice
SUBDIR += R-cran-SuppDists
SUBDIR += R-cran-Zelig

21
math/R-cran-MCMCpack/Makefile Normal file
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@ -0,0 +1,21 @@
# Created by: TAKATSU Tomonari <tota@FreeBSD.org>
# $FreeBSD$
PORTNAME= MCMCpack
DISTVERSION= 1.2-4
CATEGORIES= math
DISTNAME= ${PORTNAME}_${DISTVERSION}
MAINTAINER= tota@FreeBSD.org
COMMENT= Markov chain Monte Carlo Package
LICENSE= GPLv3
RUN_DEPENDS= R-cran-coda>0.11.3:${PORTSDIR}/math/R-cran-coda
# Actually required 4.0 or later, but at least 4.2 in the FreeBSD ports tree
USE_GCC= 4.2+
USE_R_MOD= yes
R_MOD_AUTOPLIST= yes
.include <bsd.port.mk>

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math/R-cran-MCMCpack/distinfo Normal file
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@ -0,0 +1,2 @@
SHA256 (MCMCpack_1.2-4.tar.gz) = 5c9aea9329371ab5e8488ad29aff67fbb6a4eca7e4ad25802aed168bcc0b84ba
SIZE (MCMCpack_1.2-4.tar.gz) = 493078

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math/R-cran-MCMCpack/pkg-descr Normal file
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@ -0,0 +1,11 @@
This package contains functions to perform Bayesian inference using
posterior simulation for a number of statistical models. Most
simulation is done in compiled C++ written in the Scythe Statistical
Library Version 1.0.2. All models return coda mcmc objects that can
then be summarized using the coda package. MCMCpack also contains
some useful utility functions, including some additional density
functions and pseudo-random number generators for statistical
distributions, a general purpose Metropolis sampling algorithm, and
tools for visualization.
WWW: http://cran.r-project.org/web/packages/MCMCpack/