link_significance: Estimate statistical deviations from ghype model

In ghypernet: Fit and Simulate Generalised Hypergeometric Ensembles of Graphs

Description

linkSignificance allows to estimate the statistical deviations of an observed graph from a ghype model.

Usage

linkSignificance(
  graph,
  model,
  under = FALSE,
  log.p = FALSE,
  binomial.approximation = FALSE,
  give_pvals = FALSE
)

link_significance(
  graph,
  model,
  under = FALSE,
  log.p = FALSE,
  binomial.approximation = FALSE,
  give_pvals = FALSE
)

Arguments

graph	an adjacency matrix or a igraph object.
model	a ghype model
under	boolean, estimate under-represented deviations? Default FALSE.
log.p	boolean, return log values of probabilities
binomial.approximation	boolean, force binomial? default FALSE
give_pvals	boolean, return p-values for both under and over significance?

Value

matrix of probabilities with same size as adjacency matrix.

Examples

data("adj_karate")
fullmodel <- ghype(graph = adj_karate, directed = FALSE, selfloops = FALSE)
link_significance(graph = adj_karate, model = fullmodel, under=FALSE)

ghypernet documentation built on Oct. 15, 2021, 5:14 p.m.