Module eigenvector 

Eigenvector centrality via power iteration.

Measures node importance based on the principle that connections to high-scoring nodes contribute more. Related to PageRank but without teleportation or damping.

The dominant eigenvector of the adjacency matrix gives the centrality scores. For undirected graphs, this is well-defined (Perron-Frobenius).

Structs

EigenvectorRun

Convergence details for eigenvector centrality computation.

Functions

eigenvector_centrality

Compute eigenvector centrality with default parameters (max_iter=100, tol=1e-6).

eigenvector_centrality_run

Compute eigenvector centrality with full convergence reporting.