Description Usage Arguments Value
The simplest case of for testing conditional independence is one of three variables – two to compare, and one variable upon which to condition the comparison. These function generates a Gaussian Bayesian network structure composed of three variable subnetworks of the form B <- C -> A. Intercepts are fixed at 0 and marginal variances at 1.
1 | triplet_network(m, rho)
|
rho |
the desired value of the correlation for A and B wsith C. |
Number |
of subnetworks. |
an object of bn.fit, bn.fit.gnet
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