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:
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')) |
Bug tracker:https://github.com/sshpa/bayesvl/issues
- Legends345 - Legends345 data
Last updated 3 years agofrom:c307c2e455. Checks:OK: 1 WARNING: 4. Indexed: yes.
Target | Result | Date |
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Doc / Vignettes | OK | Nov 10 2024 |
R-4.5-win | WARNING | Nov 10 2024 |
R-4.5-linux | WARNING | Nov 10 2024 |
R-4.4-win | WARNING | Nov 10 2024 |
R-4.4-mac | WARNING | Nov 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 page | Topics |
---|---|
BayesVL package for Bayesian statistical analyses in R | bayesvl-package bayesvl |
bnlearn interface for bayesvl objects | bayesvl 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 graphs | bayesvl graph utilities bayesvl graphs bvl_addArc bvl_addNode |
Plot utilities for bayesvl objects | bayesvl 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 graph | bayesvl stan bayesvl stan utilities bvl_formula bvl_model2Stan bvl_modelFit bvl_stanParams bvl_stanPriors |
Class 'bayesvl': object class of bayesvl model | bayesvl-class bvl_addArc,bayesvl-method bvl_addNode,bayesvl-method bvl_modelFit,bayesvl-method bvl_stanParams,bayesvl-method show,bayesvl-method summary,bayesvl-method |
Legends345 data | Legends345 |