bayesvl-class: Class 'bayesvl': object class of bayesvl model

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

Class bayesvl: object class of bayesvl model

Description

This object contains an object of class bayesvl, return by bayesvl.

Slots

call:

Original function call that produced the fit

nodes:

The list of nodes in model

arcs:

The list of arcs in model

pars:

List of parameters

stanfit:

Object of class stanfit

rawdata:

Observed data frame

standata:

Data used in sampling

posterior:

Coerce to a Data Frame of object of class stanfit

elapsed:

Elapsed time of MCMC simulation

Methods

show

signature(object = "bayesvl"): print the default summary for the model.

summary

Displays the model slot.

References

For documentation, case studies and worked examples, and other tutorial information visit the References section on our Github:

• github.com/sshpa/bayesvl/master/References/bvl_ug_en08.pdf

See Also

bayesvl

Examples

	# 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)

sshpa/bayesvl documentation built on June 1, 2022, 12:50 a.m.