# robin

Available on CRAN https://CRAN.R-project.org/package=robin

*ROBIN (ROBustness In Network)* is an R
package for the validation of community detection. It has a double aim:
it **studies the robustness** of a community detection
algorithm and it **compares** the robustness of **two
community detection algorithms**.

The package implements a methodology that detects if the community
structure found by a detection algorithm is statistically significant or
is a result of chance, merely due to edge positions in the network.

###### The package:

**Examine the robustness** of a community detection
algorithm against random perturbations of the original graph

**Tests the statistical difference** between the
stability measure curves created

Makes a **comparison between different community detection
algorithms** to choose the one that better fits the network of
interest

Gives a graphical **interactive
representation**

```
my_network <- system.file("example/football.gml", package="robin")
graph <- prepGraph(file=my_network, file.format="gml")
graphRandom <- random(graph=graph)
proc <- robinRobust(graph=graph, graphRandom=graphRandom, measure="vi",
method="louvain", type="independent")
plotRobin(graph=graph, model1=proc$Mean, model2=proc$MeanRandom,
legend=c("real data", "null model"), measure="vi")
```

```
#For the testing:
robinFDATest(graph=graph, model1=proc$Mean, model2=proc$MeanRandom,
measure="vi")
robinGPTest(model1=proc$Mean, model2=proc$MeanRandom)
```

```
my_network <- system.file("example/football.gml", package="robin")
graph <- prepGraph(file=my_network, file.format="gml")
comp <- robinCompare(graph=graph, method1="fastGreedy",
method2="louvain", measure="vi", type="independent")
plotRobin(graph=graph, model1=comp$Mean1, model2=comp$Mean2, measure="vi",
legend=c("fastGreedy", "louvain"), title="FastGreedy vs Louvain")
```

In this example, the Louvain algorithm fits better the network of
interest, as the curve of the stability measure varies less than the one
obtained by the Fast greedy method.

```
#For the testing:
robinFDATest(graph=graph, model1=comp$Mean1, model2=comp$Mean2, measure="vi")
robinGPTest(model1=comp$Mean1, model2=comp$Mean2)
```

## Reference

ROBustness In Network (robin): an R package for Comparison and
Validation of communities Valeria Policastro, Dario Righelli, Annamaria
Carissimo, Luisa Cutillo, Italia De Feis. The R Journal (2021)
https://journal.r-project.org/archive/2021/RJ-2021-040/index.html

## License

Copyright
(c) 2019 V. Policastro, A. Carissimo, L. Cutillo, I. De Feis and D.
Righelli.