gnu: Add r-abn.

* gnu/packages/cran.scm (r-abn): New variable.
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Ricardo Wurmus 2018-11-12 16:22:28 +01:00 committed by Ricardo Wurmus
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commit 488dc4e1e2
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@ -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.") to help insert or delete content at a specific location in the document.")
(license license:gpl3))) (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 (define-public r-snakecase
(package (package
(name "r-snakecase") (name "r-snakecase")