wpr: Weighted PageRank centrality

In wdnet: Weighted and Directed Networks

Weighted PageRank centrality

Description

Compute the weighted PageRank centrality measures of the vertices in a weighted and directed network represented through its adjacency matrix.

Usage

wpr(adj, gamma = 0.85, theta = 1, prior.info)

Arguments

adj	is an adjacency matrix of a weighted and directed network
gamma	is the damping factor; it takes 0.85 (default) if not given.
theta	is a tuning parameter leveraging node degree and strength; theta = 0 does not consider edge weight; theta = 1 (default) fully considers edge weight.
prior.info	vertex-specific prior information for restarting when arriving at a sink. When it is not given (NULL), a random restart is implemented.

Value

a list of node names with corresponding weighted PageRank scores

Note

Function wpr is an extension of function page_rank in package igraph.

References

• Zhang, P., Wang, T. and Yan, J. (2022) PageRank centrality and algorithms for weighted, directed networks with applications to World Input-Output Tables. Physica A: Statistical Mechanics and its Applications, 586, 126438.

wdnet documentation built on May 29, 2024, 9:32 a.m.