compare_to_baseline: Compare motif occurence in empirical network to occurence in...

In motifr: Motif Analysis in Multi-Level Networks

Description

This function plots a comparison of the motif counts in a given network with the motif counts in a baseline model.

Usage

compare_to_baseline(
  net,
  motifs,
  n = 10,
  lvl_attr = "sesType",
  assume_sparse = TRUE,
  model = "erdos_renyi",
  level = -1,
  ergm_model = NULL,
  directed = NULL
)

Arguments

net	network object
motifs	list of motif identifier strings
n	number of random graphs used in baseline model
lvl_attr	character vector specifying the attribute name where level information is stored in net.
assume_sparse	whether the random graphs shall be assumed to be sparse. used to find ideal counting function
model	baseline model to be used. Options are 'erdos_renyi', 'actors_choice', 'ergm', 'partial_ergm' and fixed_densities'. See vignette("random_baselines") for more details. Defaults to 'erdos_renyi'.
level	lvl_attr of the variable level for the Actor's Choice model
ergm_model	ergm model as for example fitted by calling ergm::ergm() on the empirically observed network. Needs to be supplied when model is set to ergm.
directed	whether the graph shall be treated as a directed graph. Per default (NULL), this is determined automatically using the structure of the provided network object

Details

Note that when using the Actor's Choice model this function does not choose the variable level automatically. Use the level parameter to provide a valid level.

When using ERGM the parameter net is not used. Networks to create the baseline from are sampled in R using the ergm_model parameter.

Value

data frame with one row for each motif identifier string and one row for every computed random graph

Examples

## Not run: 
compare_to_baseline(ml_net, list("1,2[I.C]", "1,2[II.C]"), directed = FALSE)

## End(Not run)

motifr documentation built on Dec. 15, 2020, 5:23 p.m.