Module hrg 

Hierarchical Random Graph (HRG) models.

A hierarchical random graph is an ensemble of undirected graphs defined via a binary tree with n leaf vertices and n-1 internal vertices labelled with connection probabilities. The probability that two leaf vertices are connected equals the probability at their lowest common ancestor.

Reference: A. Clauset, C. Moore, and M.E.J. Newman. “Hierarchical structure and the prediction of missing links in networks.” Nature 453, 98–101 (2008).

Structs

HrgDendrogram

Result of converting an HrgTree to a dendrogram graph.

HrgTree

A hierarchical random graph represented as a binary dendrogram.

Functions

from_hrg_dendrogram

Convert an HrgTree into a directed graph dendrogram.

hrg_consensus

Compute a consensus tree from MCMC samples of HRG models.

hrg_create

Create an HrgTree from a directed binary tree graph.

hrg_fit

Fit a hierarchical random graph model to a network using MCMC.

hrg_game

Generate a hierarchical random graph (alias for hrg_sample).

hrg_predict

Predict missing edges based on HRG ensemble sampling.

hrg_sample

Sample a random graph from a hierarchical random graph model.

hrg_sample_many

Sample multiple random graphs from a hierarchical random graph model.