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 uses moment
fractional Bayes factors (MFBF) and is suitable for learning sparse graphs.
The algorithm is implemented 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

Guido Consonni

Luca La Rocca

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