plotGraphs

plot the data matrix, the inferred graph and/or the true binary graph

Greedy Bayesian algorithm to fit the noisy stochastic block model to an observed sparse graph. Moreover, a graph inference procedure to recover Gaussian Graphical Model (GGM) from real data. This procedure comes with a control of the false discovery rate. The method is described in the article "Enhancing the Power of Gaussian Graphical Model Inference by Modeling the Graph Structure" by Kilian, Rebafka, and Villers (2024) <arXiv:2402.19021>.

Valentin Kilian

noisysbmGGM

Noisy Stochastic Block Model for GGM Inference

Fanny Villers

plotGraphs function

<dl><dt>dataMatrix</dt>
<dd>observed data matrix</dd>
<dt>inferredGraph</dt>
<dd>graph inferred by the multiple testing procedure via graphInference()</dd>
<dt>binaryTruth</dt>
<dd>true binary graph</dd></dl>

Arguments

plot the data matrix, the inferred graph and/or the true binary graph — plotGraphs

<dl>

<dt>dataMatrix</dt>
<dd>observed data matrix</dd>


<dt>inferredGraph</dt>
<dd>graph inferred by the multiple testing procedure via graphInference()</dd>


<dt>binaryTruth</dt>
<dd>true binary graph</dd>

</dl>

plotGraphs: plot the data matrix, the inferred graph and/or the true binary graph

Description

Usage

Value

Arguments