PageRank_H: PageRank of a Row Normalized Hyperlink Matrix

In leb-fmvz-usp/epinemo: An R Package for EPIdemiological NEtwork MOdels

PageRank of a Row Normalized Hyperlink Matrix

Description

Calculates the PageRank for an n-by-n Markov Matrix (Row Normalized Hyperlink Matrix).

Usage

PageRank_H(H, alpha = 0.85, epsilon = 1e-08, pr0, v)

Arguments

H	matrix Row Normalized Hyperlink Matrix. N-by-N sparse matrix. Output of Rnhm function.
alpha	scaling parameter in PageRank model. It must be numeric between 0 and 1 inclusive. Default = 0.85.
epsilon	convergence tolerance. Default = 1e-8.
pr0	starting vector at iteration 0 (a row vector). Usually set to rep(1/n,n).
v	personalization vector. sum(v) = 1.

Details

This function uses the power method to calculate the PageRank of a row normalized hyperlink matrix [1].

Value

Numeric vector with nodes' PageRank

References

[1] Langville AN, Meyer CD (2006). "Google's PageRank and Beyond: The Science of Search Engine Rankings." Princeton University Press, Princeton.

Examples

# Generate an arbitrary 100 by 100 adjacency matrix with zeros and ones
# Remove loops
A <- matrix(rbinom(100 * 100, 1, 0.2), ncol = 100, nrow = 100)
diag(A) <- 0

# Calculate PageRank
PageRank_H(Rnhm(A))

leb-fmvz-usp/epinemo documentation built on Nov. 27, 2022, 10:58 p.m.