dataSim200

<code>dataSim200</code> is a <code>list</code> with the adjacency matrix of a randomly generated DAG with 200 nodes and 100 edges, 10 samples generated from the DAG and 5 permutations of the nodes.

datasets

We propose an objective Bayesian algorithm for searching the space of Gaussian directed acyclic graph (DAG) models. The algorithm proposed makes use of moment fractional Bayes factors (MFBF) and thus it is suitable for learning sparse graph. The algorithm is implemented by using Armadillo: an open-source C++ linear algebra library.

Davide Altomare

FBFsearch

Algorithm for Searching the Space of Gaussian Directed Acyclic
Graph Models Through Moment Fractional Bayes Factors

dataSim200 function

<code>dataSim200</code> contains the following objects:<dl>
 <dt><code>Obs</code></dt>
<dd>List of 10 matrices (100x200) each of which with 100 observations simulated from the DAG.</dd> <dt><code>Perms</code></dt>
<dd>List of 5 matrices (1x200) each of which with a permutation of the nodes.</dd> <dt><code>TDag</code></dt>
<dd>Matrix (200x200) with the adjacency matrix of the DAG.</dd> 
</dl>

Format

DAG model with 200 nodes and 100 edges — dataSim200

<code>dataSim200</code> contains the following objects:<dl>
 <dt><code>Obs</code></dt>
<dd>List of 10 matrices (100x200) each of which with 100 observations simulated from the DAG.</dd>

 <dt><code>Perms</code></dt>
<dd>List of 5 matrices (1x200) each of which with a permutation of the nodes.</dd>

 <dt><code>TDag</code></dt>
<dd>Matrix (200x200) with the adjacency matrix of the DAG.</dd>

 
</dl>

dataSim200: DAG model with 200 nodes and 100 edges

Description

Usage

Arguments

Format

References