Description Usage Arguments Value See Also
Simulates a Gaussian Bayesian network by simulating a network structure and a random covariance matrix consistent with the I-map of the network structure, and then calculating network parameters based on the covariance matrix.
1 | simGaussianNet(num.vars, rng = c(0.5, 1.5), method = "melancon")
|
num.vars |
Number of variables/nodes |
rng |
The desired range of the eigen values in the covariance matrix. |
method |
A character string, possible values are |
An object of class bn.fit
simGaussianNet
, simBNFromCovMat
,
simDAGFromCovMat
, simNetCovariance
, simMVNData
,
randomNet
, simSparsePrecision
, simDAGFromCovMat
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