isDAG: Check Direct Acyclic Graph (DAG) Condition
In sdnet: Soft-Discretization-Based Bayesian Network Inference
Description
Usage
Arguments
Details
Value
Author(s)
Examples
Description
For a pair of node and parent lists, the function checks whether the DAG condition holds or not.
Usage
1
isDAG(lnodes, lpars)
Arguments
lnodes
a list of nodes
lpars
a list of node parents
Details
The DAG verification algorithm is based on the topological ordering of the graph nodes. If node ordering is not possible, the graph is not a DAG.
Value
A logical TRUE/FALSE value.
Author(s)
N. Balov
Examples
1
2
cnet <- cnRandomCatnet(numnodes=20, maxpars=3, numcats=2)
isDAG(lnodes=cnet@nodes, lpars=cnet@pars)
sdnet documentation built on May 2, 2019, 12:43 a.m.
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Description Usage Arguments Details Value Author(s) Examples
Description
For a pair of node and parent lists, the function checks whether the DAG condition holds or not.
Usage
1 | isDAG(lnodes, lpars)
|
Arguments
lnodes |
a list of nodes |
lpars |
a list of node parents |
Details
The DAG verification algorithm is based on the topological ordering of the graph nodes. If node ordering is not possible, the graph is not a DAG.
Value
A logical TRUE/FALSE value.
Author(s)
N. Balov
Examples
1 2 | cnet <- cnRandomCatnet(numnodes=20, maxpars=3, numcats=2)
isDAG(lnodes=cnet@nodes, lpars=cnet@pars)
|
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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