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authorRicardo Wurmus <ricardo.wurmus@mdc-berlin.de>2018-11-12 16:22:28 +0100
committerRicardo Wurmus <rekado@elephly.net>2018-11-14 15:13:20 +0100
commit488dc4e1e27327831d08cb8f33a9128dc1b7eb26 (patch)
tree5a52ee19ea575c9890404a16c80a0ec0c6150750 /gnu/packages/cran.scm
parent0c92f3734e64086599940cf32a37b4cdd3be3648 (diff)
downloadpatches-488dc4e1e27327831d08cb8f33a9128dc1b7eb26.tar
patches-488dc4e1e27327831d08cb8f33a9128dc1b7eb26.tar.gz
gnu: Add r-abn.
* gnu/packages/cran.scm (r-abn): New variable.
Diffstat (limited to 'gnu/packages/cran.scm')
-rw-r--r--gnu/packages/cran.scm37
1 files changed, 37 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index 093c51ee9a..446062cce6 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -4816,6 +4816,43 @@ be added or removed. When working with Word documents, a cursor can be used
to help insert or delete content at a specific location in the document.")
(license license:gpl3)))
+(define-public r-abn
+ (package
+ (name "r-abn")
+ (version "1.2")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (cran-uri "abn" version))
+ (sha256
+ (base32
+ "00k0razgdb5y5f62622fm7rxkcxrxg470nyyb02dvpfp60254kvs"))))
+ (build-system r-build-system)
+ (inputs
+ `(("gsl" ,gsl)))
+ (propagated-inputs
+ `(("r-cairo" ,r-cairo)
+ ("r-lme4" ,r-lme4)
+ ("r-mass" ,r-mass)
+ ("r-nnet" ,r-nnet)
+ ("r-rcpp" ,r-rcpp)
+ ("r-rcpparmadillo" ,r-rcpparmadillo)
+ ("r-rjags" ,r-rjags)))
+ (home-page "http://www.r-bayesian-networks.org")
+ (synopsis "Modelling multivariate data with additive bayesian networks")
+ (description
+ "Bayesian network analysis is a form of probabilistic graphical models
+which derives from empirical data a directed acyclic graph, DAG, describing
+the dependency structure between random variables. An additive Bayesian
+network model consists of a form of a DAG where each node comprises a
+@dfn{generalized linear model} (GLM). Additive Bayesian network models are
+equivalent to Bayesian multivariate regression using graphical modelling, they
+generalises the usual multivariable regression, GLM, to multiple dependent
+variables. This package provides routines to help determine optimal Bayesian
+network models for a given data set, where these models are used to identify
+statistical dependencies in messy, complex data.")
+ (license license:gpl2+)))
+
(define-public r-snakecase
(package
(name "r-snakecase")