bnlearn (version 2.6)

bn.var: Structure variability of Bayesian networks

Description

Measure the variability of the structure of a Bayesian network.

Usage

# first and second moments' estimation
bn.moments(data, R = 200, m = nrow(data), algorithm,
  algorithm.args = list(), reduce = NULL, debug = FALSE)
# descriptive statistics
bn.var(x, method)
# Monte Carlo test for entropy
bn.var.test(x, method, R, B, debug = FALSE)

Value

• bn.moments returns an object of class mvber.moments.

  bn.var returns a vector of two elements, the observed value of the statistic (named statistic) and its normalized equivalent (named normalized).

  bn.var.test returns an object of class htest.

References

Scutari M (2009). "Structure Variability in Bayesian Networks". ArXiv Statistics - Methodology e-prints. http://arxiv.org/abs/0909.1685.

Examples

z =  bn.moments(learning.test, algorithm = "gs", R = 100)
bn.var(z, method = "tvar")
#  statistic normalized
#    1.29060    0.34416
bn.var.test(z, method = "nvar")
#
# 	Squared Frobenius Norm
#
# data:  covariance matrix
# nvar = 0.5471, B = 5000, R = 100, p-value < 2.2e-16
# alternative hypothesis: true value is greater than 0