gtrans(sna)
gtrans()所属R语言包：sna
Compute the Transitivity of an Input Graph or Graph Stack
计算输入图形或图形堆栈的传递性
译者：生物统计家园网 机器人LoveR
描述----------Description----------
gtrans returns the transitivity of the elements of dat selected by g, using the definition of measure. Triads involving missing values are omitted from the analysis.
gtrans返回及物性的元素dat选择g，使用的定义measure。黑社会涉及缺少的值遗漏分析。
用法----------Usage----------
gtrans(dat, g=NULL, diag=FALSE, mode="digraph", measure = c("weak",
"strong", "weakcensus", "strongcensus"), use.adjacency = TRUE)
参数----------Arguments----------
参数：dat
a collection of input graphs.
输入图的集合。
参数：g
a vector indicating the graphs which are to be analyzed; by default, all graphs are analyzed.
一个矢量图形进行分析，默认情况下，所有的图形进行分析。
参数：diag
a boolean indicating whether or not diagonal entries (loops) are to be taken as valid data.
一个布尔值，表示是否对角线的项（循环）的方法，是被视为有效的数据。
参数：mode
"digraph" if directed triads are sought, or else "graph".
"digraph"，如果定向黑社会寻求，否则"graph"。
参数：measure
one of "weak" (default), "strong", "weakcensus", or "strongcensus".
"weak"（默认），"strong"，"weakcensus"或"strongcensus"之一。
参数：use.adjacency
logical; should adjacency matrices (versus sparse graph methods) be used in the transitivity computation?
逻辑，邻接矩阵（对稀疏图方法）计算的传递？
Details
详细信息----------Details----------
Transitivity is a triadic, algebraic structural constraint. In its weak form, the transitive constraint corresponds to a->b->c => a->c. In the corresponding strong form, the constraint is a->b->c <=> a->c. (Note that the weak form is that most commonly employed.) Where measure=="weak", the fraction of potentially intransitive triads obeying the weak condition is returned. With the measure=="weakcensus" setting, by contrast, the total number of transitive triads is computed. The strong versions of the measures are similar to the above, save in that the set of all triads is considered (since all are “at risk” for intransitivity).
传递性是一个三元，代数结构的约束。在其弱形式，传递的约束对应到a->b->c => a->c。在相应的强有力的形式，约束是a->b->c <=> a->c。 （请注意，弱形式，是最常用的。）在哪里measure=="weak"，返回服从弱的条件可能不及黑社会的分数。随着measure=="weakcensus"设置，相比之下，传递三合会的总数计算。 strong版本类似上述的措施是，保存在该组的所有黑社会（因为所有被认为是“有风险”不及物）。
Note that the default method used here employs matrix multiplication to calculate transitivity scores. For very large, sparse graphs, the sparse graph method (use.adjacency=FALSE) may be preferred. The latter provides much better scaling, but is significantly slower for networks of typical size due to the overhead involved (and R's highly optimized matrix operations).
请注意，这里使用的默认方法采用矩阵乘法的计算及物成绩。对于非常大的，稀疏图，稀疏图的方法（use.adjacency=FALSE）可能会是首选。后者提供了更好的缩放比例，但由于所涉及的开销（R的高度优化的矩阵运算）的典型尺寸的网络明显慢。
值----------Value----------
A vector of transitivity scores
一个向量的传递性得分
（作者）----------Author(s)----------
Carter T. Butts <a href="mailto:buttsc@uci.edu">buttsc@uci.edu</a>
参考文献----------References----------
参见----------See Also----------
triad.classify, cugtest
triad.classify，cugtest
实例----------Examples----------
#Draw some random graphs[绘制一些随机图]
g<-rgraph(5,10)
#Find transitivity scores[传递性分数]
gtrans(g)
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。
|
发表于 2012-9-30 10:54:24
