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bayesvl  

Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with 'Stan'
View on CRAN: Click here


Download and install bayesvl package within the R console
Install from CRAN:
install.packages("bayesvl")

Install from Github:
library("remotes")
install_github("cran/bayesvl")

Install by package version:
library("remotes")
install_version("bayesvl", "0.8.5")



Attach the package and use:
library("bayesvl")
Maintained by
Viet-Phuong La
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-05-24
Latest Update: 2019-05-24
Description:
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) The 'bayesvl' R package. Open Science Framework (May 18).
How to cite:
Viet-Phuong La (2019). bayesvl: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with 'Stan'. R package version 0.8.5, https://cran.r-project.org/web/packages/bayesvl. Accessed 03 Feb. 2025.
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Complete documentation for bayesvl
Functions, R codes and Examples using the bayesvl R package
Some associated functions: Legends345 . bayesvl-class . bayesvl . graphs . plots . stan . vl2bn . 
Some associated R codes: bayesvl-class.R . bayesvl-plots.R . bayesvl-templates.R . bayesvl.R . bayesvl2stan.R . utils.R .  Full bayesvl package functions and examples
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