bicm: bicm: Bipartite Configuration Model.

In KGodard1/Fastball-SourceCpp: Extracts the Backbone from Weighted Graphs

Description

bicm: Bipartite Configuration Model.

Usage

bicm(graph, tol = 1e-08, max_steps = 200, ...)

Arguments

graph	matrix, a bipartite adjacency matrix of a graph
tol	numeric, tolerance of algorithm
max_steps	numeric, number of times to run loglikelihood_prime_bicm algorithm
...	optional arguments

Details

The Bipartite Configuration Model (Saracco et. al. 2015, 2017) produces a matrix of edge specific probabilities which are used in sdsm to find the p-values of the edges in the bipartite projection. This R code is adapted from the python BiCM package by Matteo Bruno under the MIT license.

Value

matrix containing probabilities

References

python bicm: Matteo Bruno, matteo.bruno<at>imtlucca.it, https://github.com/mat701/BiCM

bicm: Saracco, F., Straka, M. J., Clemente, R. D., Gabrielli, A., Caldarelli, G., & Squartini, T. (2017). Inferring monopartite projections of bipartite networks: An entropy-based approach. New Journal of Physics, 19(5), 053022. doi: 10.1088/1367-2630/aa6b38

bicm: Saracco, F., Di Clemente, R., Gabrielli, A., & Squartini, T. (2015). Randomizing bipartite networks: The case of the World Trade Web. Scientific Reports, 5(1), 10595. doi: 10.1038/srep10595

Examples

bicm(davis)

KGodard1/Fastball-SourceCpp documentation built on Dec. 18, 2021, 2:35 a.m.