bayesvl-package {bayesvl} | R Documentation |
The R package for visually learning the graphical structures of Bayesian networks, and performing Hamiltonian MCMC with Stan through bvl_model2Stan
, bvl_modelFit
Package: | bayesvl |
Type: | Package |
Version: | 0.8.0 |
Date: | 13 May 2019 |
License: | GPL-3 |
Website: | Bayesvl |
Quan-Hoang Vuong, Viet-Phuong La
For documentation, case studies and worked examples, and other tutorial information visit the References section on our Github:
bayesvl-class
, bvl_modelFit
, bvl_model2Stan
# Design the model in directed acyclic graph
model <- bayesvl()
# add observed data nodes to the model
model <- bvl_addNode(model, "Lie", "binom")
model <- bvl_addNode(model, "B", "binom")
model <- bvl_addNode(model, "C", "binom")
model <- bvl_addNode(model, "T", "binom")
# add path between nodes
model <- bvl_addArc(model, "B", "Lie", "slope")
model <- bvl_addArc(model, "C", "Lie", "slope")
model <- bvl_addArc(model, "T", "Lie", "slope")
summary(model)