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author | tota <tota@FreeBSD.org> | 2013-04-21 07:10:25 +0800 |
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committer | tota <tota@FreeBSD.org> | 2013-04-21 07:10:25 +0800 |
commit | ec29c59accdcb9421fe7af29b20a549f6d35d9eb (patch) | |
tree | 5c7d15d739449868d10d107b4d8465c431d27160 /math | |
parent | c73662462e6a29df2fbe270a4d0c2cd5966d9c94 (diff) | |
download | freebsd-ports-gnome-ec29c59accdcb9421fe7af29b20a549f6d35d9eb.tar.gz freebsd-ports-gnome-ec29c59accdcb9421fe7af29b20a549f6d35d9eb.tar.zst freebsd-ports-gnome-ec29c59accdcb9421fe7af29b20a549f6d35d9eb.zip |
- Update to 1.3-2
- Update pkg-descr
Feature safe: yes
Diffstat (limited to 'math')
-rw-r--r-- | math/R-cran-MCMCpack/Makefile | 2 | ||||
-rw-r--r-- | math/R-cran-MCMCpack/distinfo | 4 | ||||
-rw-r--r-- | math/R-cran-MCMCpack/pkg-descr | 2 |
3 files changed, 4 insertions, 4 deletions
diff --git a/math/R-cran-MCMCpack/Makefile b/math/R-cran-MCMCpack/Makefile index 8abfbd2a68f2..4d2222feedc2 100644 --- a/math/R-cran-MCMCpack/Makefile +++ b/math/R-cran-MCMCpack/Makefile @@ -2,7 +2,7 @@ # $FreeBSD$ PORTNAME= MCMCpack -DISTVERSION= 1.3-1 +DISTVERSION= 1.3-2 CATEGORIES= math DISTNAME= ${PORTNAME}_${DISTVERSION} diff --git a/math/R-cran-MCMCpack/distinfo b/math/R-cran-MCMCpack/distinfo index a38e7d2dac4f..f13b4fd90fbf 100644 --- a/math/R-cran-MCMCpack/distinfo +++ b/math/R-cran-MCMCpack/distinfo @@ -1,2 +1,2 @@ -SHA256 (MCMCpack_1.3-1.tar.gz) = d2f445b979fe5467278abbb783661020522d2c1964d10c3109b4d2f20a99e5ff -SIZE (MCMCpack_1.3-1.tar.gz) = 491811 +SHA256 (MCMCpack_1.3-2.tar.gz) = 6aec4a38e05631e5cc42d5eddf2bc70f7623ea0ba7429b3a1641e61fdfcacec6 +SIZE (MCMCpack_1.3-2.tar.gz) = 509502 diff --git a/math/R-cran-MCMCpack/pkg-descr b/math/R-cran-MCMCpack/pkg-descr index 6ba1af935894..3caf033dd5e0 100644 --- a/math/R-cran-MCMCpack/pkg-descr +++ b/math/R-cran-MCMCpack/pkg-descr @@ -1,7 +1,7 @@ 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 +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 |