我有一个部分相关矩阵，它由正值和负值组成。我已经基于这个矩阵构建了一个网络，并想计算它的特征向量中心性度量。我正在使用 evcent 函数，但我还没有找到关于该函数如何处理输入中的负值的任何文档。任何人都可以向我推荐可以清楚解释这一点的文档、论文等吗？我似乎对这个衡量标准感到很困惑。
我把我的代码放在这里以供参考。欢迎提出任何建议。
dput(c$estimate)
structure(c(1, 0, 0.316232734476743, 0, 0, 0.159138112996994,
0.51716720800751, 0, 0, -0.171138157203412, -0.134403786032336,
0, 1, 0.762712190750185, 0, 0, 0.232310016390404, -0.453603002876671,
-0.285980739555246, 0.323373911918246, -0.291454052760697, 0,
0.316232734476743, 0.762712190750184, 1, 0.177148045172427, 0,
0, 0.268732694036394, 0.369995711033572, -0.424016516904762,
0, 0, 0, 0, 0.177148045172423, 1, 0, -0.546060128025918, 0.501507022349682,
0.566755462948541, 0.529918603580788, 0.129323096948468, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0.159138112996997, 0.232310016390404,
0, -0.546060128025919, 0, 1, 0.144007861096439, 0.301188044463455,
0.481698196186874, 0.242875135784718, 0.16146544561877, 0.51716720800751,
-0.453603002876673, 0.268732694036395, 0.501507022349684, 0,
0.144007861096441, 1, -0.350379436564998, 0, 0.332123088063892,
0, 0, -0.285980739555248, 0.369995711033577, 0.566755462948537,
0, 0.301188044463452, -0.350379436564994, 1, 0, -0.141404020322527,
0, 0, 0.323373911918248, -0.424016516904762, 0.52991860358079,
0, 0.481698196186873, 0, 0, 1, 0.192509854303764, 0, -0.171138157203416,
-0.291454052760697, 0, 0.129323096948465, 0, 0.242875135784717,
0.332123088063894, -0.141404020322526, 0.192509854303766, 1,
0, -0.134403786032336, 0, 0, 0, 0, 0.16146544561877, 0, 0, 0,
0, 1), .Dim = c(11L, 11L), .Dimnames = list(c("jpm", "gs", "ms",
"bofa", "schwab", "brk", "wf", "citi", "amex", "spgl", "pnc"),
c("jpm", "gs", "ms", "bofa", "schwab", "brk", "wf", "citi",
"amex", "spgl", "pnc")))
g <- graph_from_adjacency_matrix(c$estimate, weighted="wt", mode="undirected", diag=F)
evcent(g,directed=F)$vector