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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><title>R: Centralize a graph according to the eigenvector centrality of...</title> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <link rel="stylesheet" type="text/css" href="R.css" /> </head><body> <table width="100%" summary="page for centr_eigen {igraph}"><tr><td>centr_eigen {igraph}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Centralize a graph according to the eigenvector centrality of vertices</h2> <h3>Description</h3> <p>See <code><a href="centralize.html">centralize</a></code> for a summary of graph centralization. </p> <h3>Usage</h3> <pre> centr_eigen( graph, directed = FALSE, scale = TRUE, options = arpack_defaults, normalized = TRUE ) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>graph</code></td> <td> <p>The input graph.</p> </td></tr> <tr valign="top"><td><code>directed</code></td> <td> <p>logical scalar, whether to use directed shortest paths for calculating eigenvector centrality.</p> </td></tr> <tr valign="top"><td><code>scale</code></td> <td> <p>Whether to rescale the eigenvector centrality scores, such that the maximum score is one.</p> </td></tr> <tr valign="top"><td><code>options</code></td> <td> <p>This is passed to <code><a href="eigen_centrality.html">eigen_centrality</a></code>, the options for the ARPACK eigensolver.</p> </td></tr> <tr valign="top"><td><code>normalized</code></td> <td> <p>Logical scalar. Whether to normalize the graph level centrality score by dividing by the theoretical maximum.</p> </td></tr> </table> <h3>Value</h3> <p>A named list with the following components: </p> <table summary="R valueblock"> <tr valign="top"><td><code>vector</code></td> <td> <p>The node-level centrality scores.</p> </td></tr> <tr valign="top"><td><code>value</code></td> <td> <p>The corresponding eigenvalue.</p> </td></tr> <tr valign="top"><td><code>options</code></td> <td> <p>ARPACK options, see the return value of <code><a href="eigen_centrality.html">eigen_centrality</a></code> for details.</p> </td></tr> <tr valign="top"><td><code>centralization</code></td> <td> <p>The graph level centrality index.</p> </td></tr> <tr valign="top"><td><code>theoretical_max</code></td> <td> <p>The same as above, the theoretical maximum centralization score for a graph with the same number of vertices.</p> </td></tr> </table> <h3>See Also</h3> <p>Other centralization related: <code><a href="centr_betw_tmax.html">centr_betw_tmax</a>()</code>, <code><a href="centr_betw.html">centr_betw</a>()</code>, <code><a href="centr_clo_tmax.html">centr_clo_tmax</a>()</code>, <code><a href="centr_clo.html">centr_clo</a>()</code>, <code><a href="centr_degree_tmax.html">centr_degree_tmax</a>()</code>, <code><a href="centr_degree.html">centr_degree</a>()</code>, <code><a href="centr_eigen_tmax.html">centr_eigen_tmax</a>()</code>, <code><a href="centralize.html">centralize</a>()</code> </p> <h3>Examples</h3> <pre> # A BA graph is quite centralized g <- sample_pa(1000, m = 4) centr_degree(g)$centralization centr_clo(g, mode = "all")$centralization centr_betw(g, directed = FALSE)$centralization centr_eigen(g, directed = FALSE)$centralization # The most centralized graph according to eigenvector centrality g0 <- make_graph(c(2,1), n = 10, dir = FALSE) g1 <- make_star(10, mode = "undirected") centr_eigen(g0)$centralization centr_eigen(g1)$centralization </pre> <hr /><div style="text-align: center;">[Package <em>igraph</em> version 1.3.5 <a href="00Index.html">Index</a>]</div> </body></html>