simNetCovariance: Simulate a covariance matrix based on a Bayesian network...
In robertness/gmsim: Simulations of Graphical Models.
Description
Usage
Arguments
Value
See Also
Description
Given a Bayesian network structure, simulates a covariance matrix consistent
with the network structure, based on Gaussian assumptions.
Usage
1
simNetCovariance(net, rng)
Arguments
net
A Bayesian network structure, an object of class bn.
rng
The desired range of the eigen values in the covariance matrix.
Value
A simulated the covariance matrix consistent with the net argument. Simulated
under the Gaussian assumption.
See Also
simGaussianNet, simBNFromCovMat,
simDAGFromCovMat, simNetCovariance, simMVNData,
randomNet, simSparsePrecision, simDAGFromCovMat
robertness/gmsim documentation built on May 27, 2019, 10:32 a.m.
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Description Usage Arguments Value See Also
Description
Given a Bayesian network structure, simulates a covariance matrix consistent with the network structure, based on Gaussian assumptions.
Usage
1 | simNetCovariance(net, rng)
|
Arguments
net |
A Bayesian network structure, an object of class bn. |
rng |
The desired range of the eigen values in the covariance matrix. |
Value
A simulated the covariance matrix consistent with the net argument. Simulated under the Gaussian assumption.
See Also
simGaussianNet, simBNFromCovMat,
simDAGFromCovMat, simNetCovariance, simMVNData,
randomNet, simSparsePrecision, simDAGFromCovMat
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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