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authorwen <wen@FreeBSD.org>2011-03-07 20:04:35 +0800
committerwen <wen@FreeBSD.org>2011-03-07 20:04:35 +0800
commit0841bc7906a96181aea8c221024a09a669667eff (patch)
tree255d29f1c85703efae6c05d1fb186b9ba3ec3650 /science
parentb6f7153ee21fe920bc889ace8f1eb21c9b71f6c8 (diff)
downloadfreebsd-ports-gnome-0841bc7906a96181aea8c221024a09a669667eff.tar.gz
freebsd-ports-gnome-0841bc7906a96181aea8c221024a09a669667eff.tar.zst
freebsd-ports-gnome-0841bc7906a96181aea8c221024a09a669667eff.zip
bayesm covers many important models used in marketing and micro-econometrics
applications. The package includes: Bayes Regression (univariate or multivariate dep var), Bayes Seemingly Unrelated Regression (SUR), Binary and Ordinal Probit, Multinomial Logit (MNL) and Multinomial Probit (MNP), Multivariate Probit, Negative Binomial (Poisson) Regression, Multivariate Mixtures of Normals (including clustering), Dirichlet Process Prior Density Estimation with normal base, Hierarchical Linear Models with normal prior and covariates, Hierarchical Linear Models with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates, Hierarchical Negative Binomial Regression Models, Bayesian analysis of choice-based conjoint data, Bayesian treatment of linear instrumental variables models, and Analysis of Multivariate Ordinal survey data with scale usage heterogeneity (as in Rossi et al, JASA (01)). WWW: http://www.perossi.org/home/bsm-1
Diffstat (limited to 'science')
-rw-r--r--science/Makefile1
-rw-r--r--science/R-cran-bayesm/Makefile20
-rw-r--r--science/R-cran-bayesm/distinfo2
-rw-r--r--science/R-cran-bayesm/pkg-descr16
4 files changed, 39 insertions, 0 deletions
diff --git a/science/Makefile b/science/Makefile
index 7fddc0c0642e..0e190b2b4bba 100644
--- a/science/Makefile
+++ b/science/Makefile
@@ -7,6 +7,7 @@
SUBDIR += 2dhf
SUBDIR += InsightToolkit
SUBDIR += R-cran-AMORE
+ SUBDIR += R-cran-bayesm
SUBDIR += abinit
SUBDIR += afni
SUBDIR += at
diff --git a/science/R-cran-bayesm/Makefile b/science/R-cran-bayesm/Makefile
new file mode 100644
index 000000000000..7665ad0f9fe7
--- /dev/null
+++ b/science/R-cran-bayesm/Makefile
@@ -0,0 +1,20 @@
+# New ports collection makefile for: R-cran-bayesm
+# Date created: March 07, 2011
+# Whom: Wen Heping <wenheping@gmail.com>
+#
+# $FreeBSD$
+#
+
+PORTNAME= bayesm
+PORTVERSION= 2.2.4
+CATEGORIES= science
+PKGNAMEPREFIX= R-cran-
+DISTNAME= ${PORTNAME}_${PORTVERSION:C/\./-/g:C/-/\./1}
+
+MAINTAINER= wen@FreeBSD.org
+COMMENT= Bayesian Inference for Marketing/Micro-econometrics
+
+USE_R_MOD= yes
+R_MOD_AUTOPLIST= yes
+
+.include <bsd.port.mk>
diff --git a/science/R-cran-bayesm/distinfo b/science/R-cran-bayesm/distinfo
new file mode 100644
index 000000000000..ddf8de6c5a85
--- /dev/null
+++ b/science/R-cran-bayesm/distinfo
@@ -0,0 +1,2 @@
+SHA256 (bayesm_2.2-4.tar.gz) = 93bfcd6652106c159fa4bc12552d34dcfee7a28597c8bf64f8ca7af65b834ce4
+SIZE (bayesm_2.2-4.tar.gz) = 1766401
diff --git a/science/R-cran-bayesm/pkg-descr b/science/R-cran-bayesm/pkg-descr
new file mode 100644
index 000000000000..681ddd86a291
--- /dev/null
+++ b/science/R-cran-bayesm/pkg-descr
@@ -0,0 +1,16 @@
+bayesm covers many important models used in marketing and micro-econometrics
+applications. The package includes: Bayes Regression (univariate or
+multivariate dep var), Bayes Seemingly Unrelated Regression (SUR), Binary and
+Ordinal Probit, Multinomial Logit (MNL) and Multinomial Probit (MNP),
+Multivariate Probit, Negative Binomial (Poisson) Regression, Multivariate
+Mixtures of Normals (including clustering), Dirichlet Process Prior Density
+Estimation with normal base, Hierarchical Linear Models with normal prior and
+covariates, Hierarchical Linear Models with a mixture of normals prior and
+covariates, Hierarchical Multinomial Logits with a mixture of normals prior
+and covariates, Hierarchical Multinomial Logits with a Dirichlet Process
+prior and covariates, Hierarchical Negative Binomial Regression Models,
+Bayesian analysis of choice-based conjoint data, Bayesian treatment of linear
+instrumental variables models, and Analysis of Multivariate Ordinal survey
+data with scale usage heterogeneity (as in Rossi et al, JASA (01)).
+
+WWW: http://www.perossi.org/home/bsm-1