Package: deal 1.2-42

Claus Dethlefsen

deal: Learning Bayesian Networks with Mixed Variables

Bayesian networks with continuous and/or discrete variables can be learned and compared from data. The method is described in Boettcher and Dethlefsen (2003), <doi:10.18637/jss.v008.i20>.

Authors:Susanne Gammelgaard Bottcher, Claus Dethlefsen.

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deal_1.2-42.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
deal/json (API)

# Install 'deal' in R:
install.packages('deal', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • ksl - Health and social characteristics
  • rats - Weightloss of rats

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.39 score 1 stars 49 scripts 566 downloads 14 mentions 78 exports 0 dependencies

Last updated from:04729afd3c. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK126
linux-devel-x86_64OK94
source / vignettesOK175
linux-release-arm64OK77
linux-release-x86_64OK88
windows-devel-arm64OK222
windows-devel-x86_64OK112
windows-release-arm64OK184
windows-release-x86_64OK74
wasm-releaseOK63

Exports:addarrowaddarrowsaddrandomarrowas.networkautosearchbanlistbanlist<-cond.nodeconditionalconditional.contconditional.disccycletestdeleterandomarrowdrawnetworkelementinfindexfindleafgenlatexgenpicfilegetnetworkgettablegettrylistheuristicinsertinspectprobjointcontjointdiscjointpriorlearnlearnnodelocalmasterlocalposteriorlocalpriorlocalproblocalprob<-makenwmakesimprobmaketrylistmodelstringnetworknetworkfamilynodenodesnodes<-numbermixednwequalnwfsortperturbplot.networkplot.networkfamilyplot.nodepostpost0postcpostc0cpostccpostdistpostdist.nodeprint.networkprint.networkfamilyprint.nodeprintlineprobprob.networkprob.nodereadnetremovearrowremoverrnetworksavenetscorescore.networkscore.nodesizeturnarrowturnrandomarrowudisclikunique.networkfamily

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Greedy searchautosearch gettable heuristic
Graphical interface for editing networksdrawnetwork
From a network family, generate LaTeX outputgenlatex genpicfile
Insert/remove an arrow in networkinsert remover
Calculates the joint prior distributionjointprior
Health and social characteristicsksl
Estimation of parameters in the local probability distributionslearn
Make a suggestion for simulation probabilitiesmakesimprob
Creates the full trylistmaketrylist
Bayesian network data structurenetwork plot.network print.network
Tools for manipulating networksas.network banlist banlist<- getnetwork gettrylist makenw modelstring size
Generates and learns all networks for a set of variables.networkfamily plot.networkfamily print.networkfamily
Representation of nodesnode nodes nodes<- plot.node print.node
The number of possible networksnumbermixed
Sorts a list of networksnwfsort
Perturbs a networkperturb
Local probability distributionslocalposterior localprior localprob localprob<- prob prob.network prob.node
Weightloss of ratsrats
Reads/saves .net filereadnet savenet
Simulation of data sets with a given dependency structurernetwork
Network scorescore score.network score.node
Makes a network family unique.unique.networkfamily