closeness_w(tnet)
closeness_w()所属R语言包:tnet
Closeness centrality in a weighted network
接近中心的加权网络
译者:生物统计家园网 机器人LoveR
描述----------Description----------
This function calculates closeness scores for nodes in a weighted network based on the distance_w-function.
此函数计算接近的分数加权网络中的节点基于的distance_w功能。
用法----------Usage----------
closeness_w(net, directed=NULL, gconly=TRUE, precomp.dist=NULL, alpha=1)
参数----------Arguments----------
参数:net
A weighted edgelist
A加权EdgeList都
参数:directed
Logical: whether the edgelist is directed or undirected. Default is NULL, then the function detects this parameter.
逻辑:是否EdgeList都向或无向。默认值是NULL,那么该函数检测这个参数。
参数:gconly
Logical: whether to calculate closeness only on the main component (traditional closeness). Default is TRUE. If this parameter is set to FALSE, a closeness measure for all nodes is computed. For details, see http://toreopsahl.com/2010/03/20/closeness-centrality-in-networks-with-disconnected-components/
逻辑:是否只计算亲密的主要组成部分(传统的封闭性)。默认值是TRUE。如果这个参数设置为FALSE,亲密措施的所有节点进行计算。有关详细信息,请参阅http://toreopsahl.com/2010/03/20/closeness-centrality-in-networks-with-disconnected-components/
参数:precomp.dist
If you have already computed the distance matrix using distance_w-function, you can enter the name of the matrix-object here.
如果你已经计算的距离矩阵使用distance_w功能,您可以输入矩阵对象的名称。
参数:alpha
sets the alpha parameter in the generalised measures from Opsahl, T., Agneessens, F., Skvoretz, J., 2010. Node Centrality in Weighted Networks: Generalizing Degree and Shortest Paths. Social Networks. If this parameter is set to 1 (default), the Dijkstra shortest paths are used. The identification procedure of these paths rely simply on the tie weights and disregards the number of nodes on the paths.
alpha参数设置,在广义的措施,从OPSAHL,T.,Agneessens,Skvoretz,J.,2010。节点中央的加权网络推广的程度和最短路径。社会网络。如果这个参数设置为1(默认),使用Dijkstra最短路径。这些路径的识别程序仅仅依赖领带上的权重,而忽略路径上的节点的数量。
值----------Value----------
Returns a data.frame with three columns: the first column contains the nodes' ids, the second column contains the closeness scores, and the third column contains the normalised closeness scores (i.e., divided by N-1).
返回一个数据框有三列:第一列包含的节点的ID,第二列包含的亲密成绩,第三列包含标准化的亲密分数(即除以N-1)。
注意----------Note----------
version 1.0.0
版本1.0.0
(作者)----------Author(s)----------
Tore Opsahl; http://toreopsahl.com
参考文献----------References----------
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
注1:为了方便大家学习,本文档为生物统计家园网机器人LoveR翻译而成,仅供个人R语言学习参考使用,生物统计家园保留版权。
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