qpRndGraph(qpgraph)
qpRndGraph()所属R语言包：qpgraph
Undirected random d-regular graphs
随机无向D-正则图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Samples an undirected d-regular graph approximately uniformly at random.
样品无向D-正则图约在随机均匀。
用法----------Usage----------
qpRndGraph(p=6, d=2, R.code.only=FALSE)
参数----------Arguments----------
参数：p
number of vertices.
顶点的数目。
参数：d
degree of every vertex.
每个顶点的程度。
参数：R.code.only
logical; if FALSE then the faster C implementation is used (default); if TRUE then only R code is executed.
逻辑;如果FALSE然后用C实现更快（默认）;如果TRUE然后只R代码被执行。
Details
详情----------Details----------
This function implements the algorithm from Steger and Wormald (1999) for sampling undirected d-regular graphs from a probability distribution of all d-regular graphs on p vertices which is approximately uniform. More concretely, for all vertex degree values d that grow as a small power of p, all d-regular graphs on p vertices will have in the limit the same probability as p grows large. Steger and Wormald (1999, pg. 396) believe that for d >> sqrt(p) the resulting probability distribution will no longer be approximately uniform.
此功能实现从斯特格和沃莫尔德的（1999）取样从概率分布p个顶点上的所有D-正规的图形，这大约是统一的无向D-正则图的算法。更具体地说，所有顶点的度值d的增长作为一个小功率的p，p个顶点上的所有D-正则图，将有相同的概率为p增长大的限制。 Steger和沃莫尔德（1999年，396页）认为，D >> SQRT（P）的概率分布将不再是约均匀。
This function is provided in order to generate a random undirected graph as input to the function qpG2Sigma which samples a random covariance matrix whose inverse (aka, precision matrix) has zeroes on those cells corresponding to the missing edges in the input graph. d-regular graphs are useful for working with synthetic graphical models for two reasons: one is that d-regular graph density is a linear function of d and the other is that the minimum connectivity degree of two disconnected vertices is an upper bound of their outer connectivity (see Castelo and Roverato, 2006, pg. 2646).
此功能作为函数的输入，以生成一个随机的无向图qpG2Sigma样本随机协方差矩阵的逆（又名，精度矩阵），这些单元输入图中的边缺少相应的零。 D-正则图是有用的工作与合成图形模型的原因有两个：一个是，D-正则图的密度是D的线性函数，另一个是最低的两个断开的顶点连通度是其外层的上限连接（见卡斯特洛和Roverato，2006年，PG。2646）。
值----------Value----------
The adjacency matrix of the resulting graph.
结果图的邻接矩阵。
作者（S）----------Author(s)----------
R. Castelo and A. Roverato
参考文献----------References----------
Gaussian graphical model search from microarray data with p larger than n, J. Mach. Learn. Res., 7:2621-2650, 2006.
Combinatorics, Probab. and Comput., 8:377-396.
参见----------See Also----------
qpG2Sigma
qpG2Sigma
举例----------Examples----------
nVar <- 50 ## number of vertices[＃数量的顶点]
maxCon <- 5 ## maximum connectivity per vertex[＃最大连接每个顶点]
set.seed(123)
A <- qpRndGraph(p=nVar, d=maxCon)
summary(apply(A, 1, sum))
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 2012-2-26 11:41:14
