R: Computes distances in terms of Structural equivalence...

sedist {blockmodeling} | R Documentation

## Computes distances in terms of Structural equivalence (Lorrain and White, 1971)

### Description

The functions computed the distances in terms of Structural equivalence (Lorrain and White, 1971) between the units of a one-mode network. Several options for treating the diagonal values are supported.

### Usage

    sedist(M, method = "default", fun = "default",
       fun.on.rows = "default", handle.interaction = "switch",
       use = "pairwise.complete.obs", ...)

### Arguments

`M` | A matrix representing the (usually valued) network. For now, only one-relational networks are supported. The network must be one-mode.
`method` | The method used to compute distances - any of the methods alloed by functions dist, cor or cov (all package::stats) or just "cor" or "cov" (given as character).
`fun` | Which function should be used to comput distacnes (given as character), .
`fun.on.rows` | For non-standard function - does the function compute measure on rows (such as `cor`, `cov`,...) of the data matrix (as opposed to computing measure on columns (such as `dist`).
`handle.interaction` | How should the interaction between the vertices analysed be handled: "switch" (the default) - assumes that when comparing units i and j, M[i,i] should be compared with M[j,j] and M[i,j] with M[j,i] "ignore" (diagonal) - Diagonal is ignored "none" - the matrix is used "as is"
`use` | For use with methods "cor" and "cov", for other methods (the default option should be used if handle.interaction=="ignore"), "pairwise.complete.obs" are always used, if stats.dist.cor.cov=TRUE
`...` | Additional arguments to `fun`

### Details

If both `method` and `fun` are "default", the euclidian distances are computed. the "default" method for `fun="dist"` is "eucludian" and for `fun="cor"` "pearson".

### Value

A matrix (usually of class dist) is returned.

### Author(s)

Aleš Žiberna

### References

Batagelj, V., Ferligoj, A., Doreian, P. (1992): Direct and indirect methods for structural equivalence. Social Networks 14, 63-90.

Lorrain, F., White, H.C., 1971. Structural equivalence of individuals in social networks. Journal of Mathematical Sociology 1, 49-80.

### See Also

`dist`, `hclust`, `REGE`, `crit.fun`, `opt.par`, `opt.random.par`

### Examples

    #generating a simple network corresponding to the simple Sum of squares
    #structural equivalence with blockmodel:
    # null com
    # null null
    n<-20
    net<-matrix(NA,ncol=n,nrow=n)
    clu<-rep(1:2,times=c(5,15))
    tclu<-table(clu)
    net[clu==1,clu==1]<-rnorm(n=tclu[1]*tclu[1],mean=0,sd=1)
    net[clu==1,clu==2]<-rnorm(n=tclu[1]*tclu[2],mean=4,sd=1)
    net[clu==2,clu==1]<-rnorm(n=tclu[2]*tclu[1],mean=0,sd=1)
    net[clu==2,clu==2]<-rnorm(n=tclu[2]*tclu[2],mean=0,sd=1)

    D<-sedist(M=net)
    plot.mat(net, clu=cutree(hclust(d=D,method="ward"),k=2))

[Package blockmodeling version 0.1.9 Index]