bicm

matrix, a bipartite adjacency matrix of a graph

graph

numeric, number of times to run <a rd-options="" href="/link/loglikelihood_prime_bicm?package=backbone&version=1.4.0" data-mini-rdoc="backbone::loglikelihood_prime_bicm">loglikelihood_prime_bicm</a> algorithm

max_steps

Boolean: If <a rd-options="utils" href="/link/txtProgressBar?package=backbone&version=1.4.0&to=utils" data-mini-rdoc="utils::txtProgressBar">txtProgressBar</a> should be used to measure progress

progress

bicm: Bipartite Configuration Model.

Provides methods for extracting from a weighted graph
a binary or signed backbone that retains only the significant edges.
The user may input a weighted graph, or a bipartite graph
from which a weighted graph is first constructed via projection.
Backbone extraction methods include the stochastic degree sequence model (Neal, Z. P. (2014). <doi:10.1016/j.socnet.2014.06.001>),
hypergeometric model (Neal, Z. (2013). <doi:10.1007/s13278-013-0107-y>),
the fixed degree sequence model (Zweig, K. A., and Kaufmann, M. (2011). <doi:10.1007/s13278-011-0021-0>),
fixed column model, fixed fill model,
as well as a universal threshold method.

Rachel Domagalski

backbone

Extracts the Backbone from Weighted Graphs

Zachary Neal

Bruce Sagan

bicm function

numeric, number of times to run <a rd-options='' href='loglikelihood_prime_bicm'>loglikelihood_prime_bicm</a> algorithm

Boolean: If <a rd-options='utils' href='txtProgressBar'>txtProgressBar</a> should be used to measure progress

bicm: bicm: Bipartite Configuration Model.

Description

Usage

Arguments

Value

Details

References

Examples