abn

Package: abn
Version: 1.0
Date: 2016-01-11
Title: Modelling Multivariate Data with Additive Bayesian Networks
Authors@R: c(person("Fraser Ian", "Lewis", role = c("aut"), email = "fraseriain.lewis@uzh.ch"), person("Marta", "Pittavino", role = c("cre","ctb"), email = "marta.pittavino@math.uzh.ch"), person("Reinhard", "Furrer", role = c("ctb"), email = "reinhard.furrer@math.uzh.ch"))
Author: Fraser Ian Lewis [aut], Marta Pittavino [cre, ctb], Reinhard Furrer [ctb]
Maintainer: Marta Pittavino <marta.pittavino@math.uzh.ch>
Depends: Cairo, R (>= 2.15.1)
Imports: methods
Suggests: INLA, Rgraphviz
Additional_repositories: http://www.math.ntnu.no/inla/R/stable/
SystemRequirements: Gnu Scientific Library version >= 1.12
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 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. 'abn' 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. The additive formulation of these models is equivalent to multivariate generalised linear modelling (including mixed models with iid random effects). The usual term to describe this model selection process is structure discovery. The core functionality is concerned with model selection - determining the most robust empirical model of data from interdependent variables. Laplace approximations are used to estimate goodness of fit metrics and model parameters, and wrappers are also included to the INLA package which can be obtained from http://www.r-inla.org. It is recommended the testing version, which can be downloaded by running: source("http://www.math.ntnu.no/inla/givemeINLA-testing.R"). A comprehensive set of documented case studies, numerical accuracy/quality assurance exercises, and additional documentation are available from the abn website.
License: GPL (>= 2)
LazyData: true
URL: http://www.r-bayesian-networks.org
NeedsCompilation: yes
Packaged: 2016-01-18 10:40:15 UTC; martapit
Repository: CRAN
Date/Publication: 2016-01-18 22:20:23

Install log

* installing to library '/home/ddbj/local/lib64/R/library'
* installing *source* package 'abn' ...
** package 'abn' successfully unpacked and MD5 sums checked
checking for gsl-config... /usr/bin/gsl-config
configure: creating ./config.status
config.status: creating src/Makevars
** libs
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c buildcachematrix.c -o buildcachematrix.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c cycles.c -o cycles.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c fit_single_node.c -o fit_single_node.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c fitabn_marginals.c -o fitabn_marginals.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c mobius.c -o mobius.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c mostprobable.c -o mostprobable.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_binomial.c -o node_binomial.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_binomial_marginals_rv.c -o node_binomial_marginals_rv.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_binomial_rv.c -o node_binomial_rv.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_binomial_rv_inner.c -o node_binomial_rv_inner.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_gaussian.c -o node_gaussian.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_gaussian_marginals_rv.c -o node_gaussian_marginals_rv.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_gaussian_rv.c -o node_gaussian_rv.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_gaussian_rv_inner.c -o node_gaussian_rv_inner.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_poisson.c -o node_poisson.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_poisson_marginals_rv.c -o node_poisson_marginals_rv.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_poisson_rv.c -o node_poisson_rv.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c node_poisson_rv_inner.c -o node_poisson_rv_inner.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c searchhill.c -o searchhill.o
gcc -I/home/ddbj/local/lib64/R/include -DNDEBUG  -I/usr/local/include   -fopenmp -I/usr/include -I. -fpic  -g -O2  -c utility.c -o utility.o
gcc -shared -L/home/ddbj/local/lib64/R/lib -L/usr/local/lib64 -o abn.so buildcachematrix.o cycles.o fit_single_node.o fitabn_marginals.o mobius.o mostprobable.o node_binomial.o node_binomial_marginals_rv.o node_binomial_rv.o node_binomial_rv_inner.o node_gaussian.o node_gaussian_marginals_rv.o node_gaussian_rv.o node_gaussian_rv_inner.o node_poisson.o node_poisson_marginals_rv.o node_poisson_rv.o node_poisson_rv_inner.o searchhill.o utility.o -fopenmp -L/usr/lib/x86_64-linux-gnu -lgsl -lgslcblas -lm -L/home/ddbj/local/lib64/R/lib -lR
installing to /home/ddbj/local/lib64/R/library/abn/libs
** R
** data
*** moving datasets to lazyload DB
** inst
** preparing package for lazy loading
** help
*** installing help indices
  converting help for package 'abn'
    finding HTML links ... done
    abninla-internal                        html  
    build_score_cache                       html  
    dag_ex0                                 html  
    dag_ex1                                 html  
    dag_ex2                                 html  
    dag_ex3                                 html  
    dag_ex4                                 html  
    dag_ex5                                 html  
    dag_ex6                                 html  
    dag_ex7                                 html  
    fitabn                                  html  
    mostprobable                            html  
    pigs.vienna                             html  
    search_hillclimber                      html  
    tographviz                              html  
    var33                                   html  
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (abn)
Making 'packages.html' ... done