multiplex_page_rank: Calculate Multiplex PageRank

In pageRank: Temporal and Multiplex PageRank for Gene Regulatory Network Analysis

Description

Calculate multiplex PageRank following defination by Halu et al.

Usage

multiplex_page_rank(graph, ..., beta = 1, gamma = 1, damping = 0.85)

Arguments

graph	(igraph) The base graph with pagerank and name as vertex attributes.
...	(igraph) Supporter graphs with pagerank and name as vertex attributes.
beta	(numeric) Parameters for adjusting supporter graph PageRank values. For the same nodes, PageRank values from different supporter graphs will first be multiplicated. The products will then be exponentiate by beta and gamma, as outgoing edge weights and personalizations of the base graph. Four special multiplex PageRank forms are defined by varying (beta, gamma), including additive (0, 1), multiplicative (1, 0), combined (1, 1) and neutral (0, 0).
gamma	(numeric) Parameters for adjusting supporter graph PageRank values. For the same nodes, PageRank values from different supporter graphs will first be multiplicated. The products will then be exponentiate by beta and gamma, as outgoing edge weights and personalizations of the base graph. Four special multiplex PageRank forms are defined by varying (beta, gamma), including additive (0, 1), multiplicative (1, 0), combined (1, 1) and neutral (0, 0).
damping	(numeric) Damping factor.

Value

(numeric) Multiplex PageRank values.

Author(s)

DING, HONGXU ([e-mail])

References

Halu, Arda, et al. "Multiplex pagerank." PloS one 8.10 (2013).

Examples

library(igraph)
set.seed(1)
graph1 <- igraph::erdos.renyi.game(100, 0.01, directed = TRUE)
igraph::V(graph1)$name <- 1:100
igraph::V(graph1)$pagerank <- igraph::page_rank(graph1)$vector
set.seed(2)
graph2 <- igraph::erdos.renyi.game(100, 0.01, directed = TRUE)
igraph::V(graph2)$name <- 1:100
igraph::V(graph2)$pagerank <- igraph::page_rank(graph2)$vector
multiplex_page_rank(graph1, graph2)

pageRank documentation built on Nov. 8, 2020, 6:52 p.m.