Package: bayesvl 1.0

bayesvl: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with 'Stan'

Provides users with its associated functions for pedagogical purposes in visually learning Bayesian networks and Markov chain Monte Carlo (MCMC) computations. It enables users to: a) Create and examine the (starting) graphical structure of Bayesian networks; b) Create random Bayesian networks using a dataset with customized constraints; c) Generate Stan code for structures of Bayesian networks for sampling the data and learning parameters; d) Plot the network graphs; e) Perform Markov chain Monte Carlo computations and produce graphs for posteriors checks. The package refers to one reference item, which describes the methods and algorithms: Vuong, Quan-Hoang and La, Viet-Phuong (2019) <doi:10.31219/osf.io/w5dx6> The 'bayesvl' R package. Open Science Framework (May 18).

Authors:Viet-Phuong La [aut, cre], Quan-Hoang Vuong [aut]

bayesvl_1.0.tar.gz
bayesvl_1.0.zip(r-4.5)bayesvl_1.0.zip(r-4.4)
bayesvl_1.0.tgz(r-4.4-any)
bayesvl_1.0.tar.gz(r-4.5-noble)bayesvl_1.0.tar.gz(r-4.4-noble)
bayesvl_1.0.tgz(r-4.4-emscripten)
bayesvl.pdf |bayesvl.html
bayesvl/json (API)

# Install 'bayesvl' in R:
install.packages('bayesvl', repos = c('https://sshpa.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/sshpa/bayesvl/issues

Datasets:

On CRAN:

bayesianmcmc

4.70 score 20 stars 3 scripts 207 downloads 5 mentions 37 exports 63 dependencies

Last updated 3 years agofrom:c307c2e455. Checks:OK: 1 WARNING: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-winWARNINGNov 10 2024
R-4.5-linuxWARNINGNov 10 2024
R-4.4-winWARNINGNov 10 2024
R-4.4-macWARNINGNov 10 2024

Exports:bayesvlbvl_addArcbvl_addNodebvl_bnBarchartbvl_bnBayesbvl_bnPlotbvl_bnScorebvl_bnStrengthbvl_compareLoobvl_compareWAICbvl_formulabvl_model2Stanbvl_modelDatabvl_modelFitbvl_plotAcbvl_plotAcfbvl_plotAcf_Barbvl_plotAcfsbvl_plotAreasbvl_plotDensitybvl_plotDensity2dbvl_plotDensOverlaybvl_plotDiagbvl_plotGelmanbvl_plotGelmansbvl_plotIntervalsbvl_plotMCMCDiagbvl_plotPairsbvl_plotParamsbvl_plotPPCbvl_plotTestbvl_plotTracebvl_stanLikelihoodbvl_stanLoobvl_stanParamsbvl_stanPriorsbvl_stanWAIC

Dependencies:abindbackportsbayesplotBHbnlearncallrcheckmateclicodacolorspacedescdistributionaldplyrfansifarvergenericsggplot2ggridgesgluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigplyrposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstanscalesStanHeadersstringistringrtensorAtibbletidyselectutf8vctrsviridisviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
BayesVL package for Bayesian statistical analyses in Rbayesvl-package bayesvl
bnlearn interface for bayesvl objectsbayesvl bnlearn bayesvl bnlearn utilities bvl_bnBarchart bvl_bnBarchart,bayesvl-method bvl_bnBayes bvl_bnBayes,bayesvl-method bvl_bnPlot,bayesvl-method bvl_bnScore bvl_bnScore,bayesvl-method bvl_bnStrength bvl_bnStrength,bayesvl-method
Utilities to manipulate graphsbayesvl graph utilities bayesvl graphs bvl_addArc bvl_addNode
Plot utilities for bayesvl objectsbayesvl plot utilities bayesvl plots bvl_bnPlot bvl_plotAcfs bvl_plotAreas bvl_plotDensity bvl_plotDensity2d bvl_plotDiag bvl_plotGelman bvl_plotGelmans bvl_plotIntervals bvl_plotPairs bvl_plotParams bvl_plotTest bvl_plotTrace
Build RStan models from directed acyclic graphbayesvl stan bayesvl stan utilities bvl_formula bvl_model2Stan bvl_modelFit bvl_stanParams bvl_stanPriors
Class 'bayesvl': object class of bayesvl modelbayesvl-class bvl_addArc,bayesvl-method bvl_addNode,bayesvl-method bvl_modelFit,bayesvl-method bvl_stanParams,bayesvl-method show,bayesvl-method summary,bayesvl-method
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