closeness(sna)
closeness()所属R语言包：sna
Compute the Closeness Centrality Scores of Network Positions
计算接近中心得分的网络位置
译者：生物统计家园网 机器人LoveR
描述----------Description----------
closeness takes one or more graphs (dat) and returns the closeness centralities of positions (selected by nodes) within the graphs indicated by g. Depending on the specified mode, closeness on directed or undirected geodesics will be returned; this function is compatible with centralization, and will return the theoretical maximum absolute deviation (from maximum) conditional on size (which is used by centralization to normalize the observed centralization score).
closeness，返回需要一个或多个图形（dat）和接近中心性的位置（选择nodes）内的图形表示g。根据指定的模式，接近向或无向的测地线将被返回，这个功能是兼容centralization，将返回的理论最大绝对偏差（最大）有条件的大小（它是由<X >标准化集中观察到的得分）。
用法----------Usage----------
closeness(dat, g=1, nodes=NULL, gmode="digraph", diag=FALSE,
tmaxdev=FALSE, cmode="directed", geodist.precomp=NULL,
rescale=FALSE, ignore.eval=TRUE)
参数----------Arguments----------
参数：dat
one or more input graphs.
一个或多个输入图表。
参数：g
integer indicating the index of the graph for which centralities are to be calculated (or a vector thereof). By default, g=1.
整数，指示其中中心性计为（或它们的向量）的曲线图的索引。默认情况下，g= 1。
参数：nodes
list indicating which nodes are to be included in the calculation. By default, all nodes are included.
列出指示哪些节点要被包括在计算中。默认情况下，所有的节点都包括在内。
参数：gmode
string indicating the type of graph being evaluated. "digraph" indicates that edges should be interpreted as directed; "graph" indicates that edges are undirected. gmode is set to "digraph" by default.
的图表类型的字符串，表示正在评估中。表明边缘应被解释为指示“有向图”，“图形”表明边缘是无向。 gmode设置为默认情况下，“有向图”。
参数：diag
boolean indicating whether or not the diagonal should be treated as valid data. Set this true if and only if the data can contain loops. diag is FALSE by default.
布尔值，表示是否对角线应被视为有效的数据。设置这是真的，当且仅当数据可以包含循环。 diag是FALSE默认情况下。
参数：tmaxdev
boolean indicating whether or not the theoretical maximum absolute deviation from the maximum nodal centrality should be returned. By default, tmaxdev==FALSE.
布尔值，表示是否从最大的节点的中心性的理论最大绝对偏差应返回。默认情况下，tmaxdev==FALSE。
参数：cmode
string indicating the type of closeness centrality being computed (distances on directed or undirected pairs, or an alternate measure).
字符串，表示接近中心的类型计算（距离向或无向对，或替代措施）。
参数：geodist.precomp
a geodist object precomputed for the graph to be analyzed (optional)
一个geodist对象的预计算的图形进行分析（可选）
参数：rescale
if true, centrality scores are rescaled such that they sum to 1.
如果为true，中心的分数重新调整，他们总结到1。
参数：ignore.eval
logical; should edge values be ignored when calculating geodesics?
逻辑，边缘值计算测地线时被忽略吗？
Details
详细信息----------Details----------
The closeness of a vertex v is defined as
接近顶点v被定义为
C_C(v) = (|V(G)|-1)/sum( d(v,i), i in V(G), i!=v )</i>
C_C（V）=（| V（G）-1）/ SUM（D（V，I），我在V（G），I！= V）</ I>
where d(i,j) is the geodesic distance between i and j (where defined). Closeness is ill-defined on disconnected graphs; in such cases, this routine substitutes Inf. It should be understood that this modification is not canonical (though it is common), but can be avoided by not attempting to measure closeness on disconnected graphs in the first place! Intuitively, closeness provides an index of the extent to which a given vertex has short paths to all other vertices in the graph; this is one reasonable measure of the extent to which a vertex is in the “middle” of a given structure.
d(i,j)是i和j（如定义）的测地线之间的距离。封闭性是不确定的，不连通图，在这种情况下，该例程的替代品Inf。应该理解的是，本变形例中是不规范（虽然它是常见的），但可避免不尝试测量接近断开在首位图！直观地说，亲近提供了一个指数在何种程度上给定的顶点有短的路径图中的所有其他顶点，这是一个合理的措施在何种程度上的顶点是在给定结构的“中间”的。
An alternate form of closeness (apparently due to Gil and Schmidt (1996)) is obtained by taking the sum of the inverse distances to each vertex, i.e.
逆距离的总和到每个顶点，即通过以下方式获得的亲密度（显然是由于Gil和施密特（1996））的另一种形式
C_C(v) = sum( 1/d(v,i), i in V(G), i!=v )/(|V(G)|-1).</i> This measure correlates well with the standard form of closeness where both are well-defined, but lacks the latter's pathological behavior on disconnected graphs. Computation of alternate closeness may be performed via the argument cmode="suminvdir" (directed case) and cmode="suminvundir" (undirected case). The corresponding arguments cmode="directed" and cmode="undirected" return the standard closeness scores in the directed or undirected cases (respectively). Although treated here as a measure of closeness, this index was originally intended to capture power or efficacy; in its original form, the Gil-Schmidt power index is a renormalized version of the above. Specifically, let R(v,G) be the set of vertices reachable by v in V \ v. Then the Gil-Schmidt power index is defined as
C_C（V）= SUM（1次/ d（V，I），我在V（G），I！= V）/（| V（G）| -1）。</ I>这项措施相关的标准的形式亲近的两个定义，但缺乏后者的病态行为不连通图。通过参数cmode="suminvdir"（指示的情况下）和cmode="suminvundir"（无向的情况下），可进行计算的替代亲密。相应的参数cmode="directed"和cmode="undirected"返回标准接近的分数在向或无向的情况下（分别）。虽然在这里治疗的封闭性作为衡量，该指数最初是打算夺取权力或疗效;在其原来的形式，的吉尔 - 施密特电源的指数是一个重整化以上的版本。具体来说，我们R(v,G)是一系列的顶点到达v中V \ v。然后，的吉尔 - 施密特电源的指数被定义为
C_GS(v) = sum( 1/d(v,i), i in R(v,G) )/|R(v,G)|.</i>
C_GS（V）= SUM（1次/ d（V，I），我在R（V，G））/ R（V，G）。</ I>
值----------Value----------
A vector, matrix, or list containing the closeness scores (depending on the number and size of the input graphs).
含有的接近程度分数（取决于上的输入图形的数量和大小）的向量，矩阵，或列表。
注意----------Note----------
Judicious use of geodist.precomp can save a great deal of time when computing multiple path-based indices on the same network.
明智地使用geodist.precomp计算时，可以节省大量的时间在同一网络上的多个路径为基础的指数。
（作者）----------Author(s)----------
Carter T. Butts, <a href="mailto:buttsc@uci.edu">buttsc@uci.edu</a>
参考文献----------References----------
Gil, J. and Schmidt, S. (1996). “The Origin of the Mexican Network of Power”. Proceedings of the International Social Network Conference, Charleston, SC, 22-25.
Sinclair, P.A. (2007). “” Social Networks, 29, 81-92.
参见----------See Also----------
centralization
centralization
实例----------Examples----------
g<-rgraph(10) #Draw a random graph with 10 members[绘制一个随机的10名成员组成的图，]
closeness(g) #Compute closeness scores[计算亲密成绩]
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。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-30 10:49:08
