ccdrFit-class: ccdrFit class
In itsrainingdata/ccdr: CCDr Algorithm for Learning Sparse Gaussian Bayesian Networks.
Description
Main class for representing DAG estimates: Represents a single DAG estimate in the solution path.
Generally speaking, these estimates should be wrapped up in a ccdrPath-class object, but
can be handled separately if desired (be careful!).
Slots
edges(edgeList) Edge list of estimated DAG (see edgeList-class).
lambda(numeric) Value of lambda for this estimate.
nedge(integer) Number of edges in this estimate.
pp(integer) Number of nodes.
nn(integer) Number of observations this estimate was based on.
time(numeric) Time in seconds to generate this estimate.
Methods
get.adjacency.matrix
num.nodes, num.edges, num.samples
itsrainingdata/ccdr documentation built on May 18, 2019, 7:12 a.m.
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Description
Main class for representing DAG estimates: Represents a single DAG estimate in the solution path.
Generally speaking, these estimates should be wrapped up in a ccdrPath-class object, but
can be handled separately if desired (be careful!).
Slots
edges(edgeList) Edge list of estimated DAG (see
edgeList-class).lambda(numeric) Value of lambda for this estimate.
nedge(integer) Number of edges in this estimate.
pp(integer) Number of nodes.
nn(integer) Number of observations this estimate was based on.
time(numeric) Time in seconds to generate this estimate.
Methods
get.adjacency.matrix
num.nodes, num.edges, num.samples
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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