initialization: initialization
In jdwilson4/MultilayerExtraction:

Description Usage Arguments Details Value Author(s) References

Function that generates randomly selected neighborhood vertex-layer sets to begin the multilayer.extraction algorithm.

1	initialization(adjacency, prop.sample, m, n)

`adjacency:`	a list object whose tth entry is an adjacency matrix representing the tth layer of a multilayer network.
`prop.sample:`	the proportion of vertices one would like to search over for initialization. Example: prop.sample = 0.05 specifies that one will obtain 0.05 * n randomly selected vertex neighborhoods for initialization, where n = number of nodes in each layer.

A neighborhood of vertex u is defined as the collection of vertices that have higher than the mean connectivity of vertex u, when aggregated across layers. The chosen layer set is a random sample of size m/2.

neighborhoods: a list object of length prop.sample * n, where each entry contains a vertex set and layer set from which multilayer.extraction can be run.

James D. Wilson

Wilson, James D., Palowitch, John, Bhamidi, Shankar, and Nobel, Andrew B. (2016) "Significance based extraction in multilayer networks with heterogeneous community structure."

jdwilson4/MultilayerExtraction documentation built on May 18, 2019, 11:39 p.m.