findPath

Finds one path between two nodes of a graph.

graphs

Provides functions for defining
mixed graphs containing three types of edges, directed,
undirected and bi-directed, with possibly multiple edges.
These graphs are useful because they capture fundamental
independence structures in multivariate distributions
and in the induced distributions after marginalization
and conditioning.
The package is especially concerned with Gaussian graphical
models for
(i) ML estimation for directed acyclic graphs, undirected and
bi-directed graphs and ancestral graph models
(ii) testing several conditional independencies
(iii) checking global identification of DAG Gaussian models
with one latent variable
(iv) testing Markov equivalences and generating Markov
equivalent graphs of specific types.

Giovanni M Marchetti

Graphical Markov Models with Mixed Graphs

Giovanni M. Marchetti

Mathias Drton

Kayvan Sadeghi

findPath function

<dl> <dt>amat</dt>
<dd>a square Boolean matrix with dimnames, the adjacency matrix of a graph.</dd> <dt>st</dt>
<dd>an integer, the starting node.</dd> <dt>en</dt>
<dd>an integer, the ending node.</dd> <dt>path</dt>
<dd>a vector of integers, used in recursive calls. At the
 beginning is <code>NULL</code>. It should not be modified by the user.</dd></dl>

Arguments

Giovanni M. Marchetti, translating the original Python
 code (see references).

Author

Finding paths — findPath

<dl>

 <dt>amat</dt>
<dd>a square Boolean matrix with dimnames, the adjacency matrix of a graph.</dd>

 <dt>st</dt>
<dd>an integer, the starting node.</dd>

 <dt>en</dt>
<dd>an integer, the ending node.</dd>

 <dt>path</dt>
<dd>a vector of integers, used in recursive calls. At the
 beginning is <code>NULL</code>. It should not be modified by the user.</dd>

</dl>

findPath: Finding paths

Description

Usage

Value

Arguments

Author

References

See Also

Examples