triplet_network: Gaussian Network Comprised of 3-Node Subnetworks

Description Usage Arguments Value

Description

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.

Usage

1

Arguments

rho

the desired value of the correlation for A and B wsith C.

Number

of subnetworks.

Value

an object of bn.fit, bn.fit.gnet


robertness/bninfo documentation built on May 27, 2019, 10:32 a.m.