simBNFromCovAndDAG: Simulate a Bayesian network from a DAG and covariance matrix

Description Usage Arguments Value See Also

View source: R/simulation.R

Description

Given a covariance matrix and a directed acyclic graph structure, simulates a fully parameterized Guassian Bayesian network consistent with the covariance matrix.

Usage

1
simBNFromCovAndDAG(dag, cov.mat)

Arguments

dag

A object of class bn, with no undirected edges.

cov.mat

A positive definate matrix.

Value

An object of class bn.fit

See Also

simGaussianNet, simBNFromCovMat, simDAGFromCovMat, simNetCovariance, simMVNData, randomNet, simSparsePrecision, simDAGFromCovMat


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