| bayesvl bnlearn utilities {bayesvl} | R Documentation |
bnlearn interface for bayesvl objects
Description
Provides the interface to the functions in the bnlearn package for network diagnostics of an object of class bayesvl.
Usage
# Interface to bn.fit function to fit the parameters of
# a Bayesian network conditional on its structure.
bvl_bnBayes(dag, data = NULL, method = "bayes", iss = 10, ...)
# Interface to bnlearn score function to compute the score of the Bayesian network.
bvl_bnScore(dag, data = NULL, ...)
# Interface to arc.strength function to measure the strength of the probabilistic
# relationships expressed by the arcs of a Bayesian network.
bvl_bnStrength(dag, data = NULL, criterion = "x2", ...)
# Interface to bn.fit.barchart function to plot fit
# the parameters of a Bayesian network conditional on its structure.
bvl_bnBarchart(dag, data = NULL, method = "bayes", iss = 10, ...)
Arguments
dag |
an object of class |
data |
a data frame containing the variables in the model. |
method |
a character string, either mle for Maximum Likelihood parameter estimation or bayes for Bayesian parameter estimation (currently implemented only for discrete data). |
iss |
a numeric value, the imaginary sample size used by the bayes method to estimate the conditional probability tables associated with discrete nodes |
criterion |
a character string, the method using for measuring |
... |
extra arguments from the generic method |
Value
bvl_bnScore() return a number, value of score.
Author(s)
La Viet-Phuong, Vuong Quan-Hoang
References
For documentation, case studies and worked examples, and other tutorial information visit the References section on our Github: