create the design matrix for the network analysis
创建设计矩阵的网络分析
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Add intercept (column of ones) and degree-based covariates (if model is for sociality effects) to a user-supplied (default is NULL) edge covariates matrix of size N^2 rows and C columns where C is the number of covariates. Node covariates may be converted to difference-between-pairs for edges.
添加用户提供的(默认值是NULL)的边缘大小为N ^ 2列和C列,其中C是协变量的协变量矩阵列的截距()和程度的协变量(如果模型是社会性的影响)。可被转换成差值之间的对边缘节点的协变量。
用法----------Usage----------
参数----------Arguments----------
参数:N
number of nodes
的节点数量
参数:model
model; may be "plain", "rreceiver", "rsender" or "rsocial". See Details.
模型可能是“普通”,“rreceiver”,“rsender”或“rsocial的”。查看详细信息。
参数:Y
adjacency matrix
邻接矩阵
参数:edgecovs
optional additional covariate / attribute data on the edges
可选的附加的协变量/属性数据的边缘上
参数:nodecovs
optional additional covariate / attribute data on the nodes
可选的额外的协变量/属性数据的节点上
Details
详细信息----------Details----------
Can be used to construct design matrices with edge covariates or node covariates and / or sociality effects. "rreceiver", "rsender" and "rsocial" model random social effects. Node covariates are differenced and treated as edge covariates.
可被用来构造设计矩阵与边缘或节点协变量的协变量和/或社会性的影响。 “rreceiver”,“rsender”和“rsocial的”模型随机的社会效果。差和节点协变量视为边缘的协变量。
值----------Value----------
An edge design matrix that is Pe x N^2 and a node design matrix that is Pn x N where Pe is the number of edge covariates and Pn is the number of node covariates.
先进的设计矩阵,它是PE X N ^ 2和节点的设计矩阵,它是Pn×N个,其中PE边缘的协变量的数量和Pn的节点的变量是。