This vignette illustrates the use of the {shinySbm} package which is
a shiny based graphical user interface (GUI) of the {sbm} package. These
packages are made to apply Stochastic Block Models on
network dataset. This dataset can be in two format: edges list and
connection matrix. First we will see how to use the shiny application in
the package. And in the second part we will see how to use the external
functions as plotSbm()
and visSbm()
.
shinySbmApp()
shinySbmApp() function contain a {shiny} application which help to use and help to learn the basics of {sbm} package. Users can import their data inside it and apply Stochastic Block Models. They can transform network data from edges list to connection matrix. Once the SBM ran, users can explore the different number of groups selected by {sbm}. They can get models outputs as: table of parameters, plots, interactive network visuals, automatic reports (pdf or html) (French or English), R script to repeat the analysis outside of the app and tables of block attributions.
The following code show how to run shinySbmApp()
from
your R console.
When this is done your browser should load this page. From this page you can import your dataset by clicking on the Browse button in embedded in red.
When you load it, the install helper (1) can show advice to adjust the importation. For example here, we imported this set as an Adjacency or Incidence matrix but as we can see in (2), we imported an Edges list. So, we need to change the nature of imported data.