hammingDist

Computes the Hamming distance between two graph objects.

 Hamming distance 

The code computes the structural intervention distance (SID) between a true directed acyclic graph (DAG) and an estimated DAG. Definition and details about the implementation can be found in J. Peters and P. Bühlmann: "Structural intervention distance (SID) for evaluating causal graphs", Neural Computation 27, pages 771-799, 2015 <doi:10.1162/NECO_a_00708>.

Fred Gruber

Structural Intervention Distance

Jonas Peters

hammingDist function

<dl> <dt>G1</dt>
<dd>p x p adjacency matrix of the first graph.</dd> <dt>G2</dt>
<dd>p x p adjacency matrix of the second graph.</dd> <dt>allMistakesOne</dt>
<dd>boolean variable (TRUE/FALSE) that indicates whether all mistakes should be counted as one. E.g., if it is set to FALSE the Hamming distance between X -&gt; Y and X &lt;- Y is two and one if it set to TRUE.</dd></dl>

Arguments

Jonas Peters &lt;jonas.peters@tuebingen.mpg.de&gt;

Author

Hamming Distance — hammingDist

<dl>

 <dt>G1</dt>
<dd>p x p adjacency matrix of the first graph.</dd>

 <dt>G2</dt>
<dd>p x p adjacency matrix of the second graph.</dd>

 <dt>allMistakesOne</dt>
<dd>boolean variable (TRUE/FALSE) that indicates whether all mistakes should be counted as one. E.g., if it is set to FALSE the Hamming distance between X -&gt; Y and X &lt;- Y is two and one if it set to TRUE.</dd>

</dl>

hammingDist: Hamming Distance

Description

Usage

Value

Arguments

Author

Details

See Also