lp_hrg: Link prediction with the HRG model

Description Usage Arguments Value Author(s) References Examples

View source: R/link_predictors.R

Description

Given a network of interest, it computes the likelihood score of interaction, for all disconnected node pairs, based on a Hierarchical Random Graph model (HRG).

Usage

1
lp_hrg(g, samples = 1000)

Arguments

g

igraph; The network of interest.

samples

integer; Number of HRG models to consider.

Value

Tibble with the following columns:

nodeA

The ID of a network node.

nodeB

The ID of a network node.

scr

The likelihood score of interaction for the node pair.

Author(s)

Gregorio Alanis-Lobato galanisl@uni-mainz.de

References

Clauset, A. et al. (2008) Hierarchical structure and the prediction of missing links in networks. Nature 453(7191):98-101

Examples

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# Apply the HRG link predictor to the Zachary Karate Club network
hrg <- lp_hrg(g = karate_club, samples = 100)

galanisl/LinkPrediction documentation built on May 17, 2019, 12:10 p.m.