robinRobust: robinRobust

In robin: ROBustness in Network

robinRobust

Description

This functions implements a procedure to examine the stability of the partition recovered by some algorithm against random perturbations of the original graph structure.

Usage

robinRobust(
  graph,
  graphRandom,
  method = c("walktrap", "edgeBetweenness", "fastGreedy", "louvain", "spinglass",
    "leadingEigen", "labelProp", "infomap", "optimal", "other"),
  FUN = NULL,
  measure = c("vi", "nmi", "split.join", "adjusted.rand"),
  type = c("independent", "dependent"),
  directed = FALSE,
  weights = NULL,
  steps = 4,
  spins = 25,
  e.weights = NULL,
  v.weights = NULL,
  nb.trials = 10,
  verbose = TRUE
)

Arguments

graph	The output of prepGraph.
graphRandom	The output of random function.
method	The clustering method, one of "walktrap", "edgeBetweenness", "fastGreedy", "louvain", "spinglass", "leadingEigen", "labelProp", "infomap", "optimal".
FUN	in case the @method parameter is "other" there is the possibility to use a personal function passing its name through this parameter. The personal parameter has to take as input the @graph and the @weights (that can be NULL), and has to return a community object.
measure	The stability measure, one of "vi", "nmi", "split.join", "adjusted.rand" all normalized and used as distances. "nmi" refers to 1- nmi and "adjusted.ran" refers to 1-adjusted.rand.
type	The type of robin construction, dependent or independent procedure.
directed	This argument is settable only for "edgeBetweenness" method.
weights	this argument is not settable for "infomap" method.
steps	this argument is settable only for "leadingEigen"and"walktrap" method.
spins	This argument is settable only for "infomap" method.
e.weights	This argument is settable only for "infomap" method.
v.weights	This argument is settable only for "infomap" method.
nb.trials	This argument is settable only for "infomap" method.
verbose	flag for verbose output (default as TRUE).

Value

A list object with two matrices: - the matrix "Mean" with the means of the procedure for the graph - the matrix "MeanRandom" with the means of the procedure for the random graph.

Examples

my_file <- system.file("example/football.gml", package="robin")
graph <- prepGraph(file=my_file, file.format="gml")
graphRandom <- random(graph=graph)
robinRobust(graph=graph, graphRandom=graphRandom, method="louvain",
measure="vi",type="independent")

robin documentation built on May 17, 2022, 1:07 a.m.