clu {blockmodeling} | R Documentation |
Function for extraction of clu (partition), all best clus (partitions), IM (image or blockmodel) and err (total error or inconsistency) for objects, returend by functions opt.par
, opt.random.par
, opt.these.par
, and check.these.par
clu(res, which = 1, ...) IM(res, which = 1, ...) err(res, ...) partitions(res)
res |
Resoult of function opt.par , opt.random.par , opt.these.par , or check.these.par |
which |
From which (if there are more than one) "best" solution whould the element be extracted. Warning! which grater than the number of "best" partitions produces an error. |
... |
Not used |
The desired element.
Aleš Žiberna
ŽIBERNA, Aleš (2006): Generalized Blockmodeling of Valued Networks. Social Networks, Jan. 2007, vol. 29, no. 1, 105-126. http://dx.doi.org/10.1016/j.socnet.2006.04.002.
ŽIBERNA, Aleš. Direct and indirect approaches to blockmodeling of valued networks in terms of regular equivalence. J. math. sociol., 2008, vol. 32, no. 1, 57-84. http://www.informaworld.com/smpp/content?content=10.1080/00222500701790207.
DOREIAN, Patrick, BATAGELJ, Vladimir, FERLIGOJ, Anuška (2005): Generalized blockmodeling, (Structural analysis in the social sciences, 25). Cambridge [etc.]: Cambridge University Press, 2005. XV, 384 p., ISBN 0-521-84085-6.
crit.fun
, check.these.par
, opt.random.par
, opt.these.par
, plot.opt.par
n<-8 #if larger, the number of partitions increases dramaticaly, #as does if we increase the number of clusters net<-matrix(NA,ncol=n,nrow=n) clu<-rep(1:2,times=c(3,5)) 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) #we select a random parition and then optimise it all.par<-nkpartitions(n=n, k=length(tclu)) #forming the partitions all.par<-lapply(apply(all.par,1,list),function(x)x[[1]]) # to make a list out of the matrix res<-opt.par(M=net, clu=all.par[[sample(1:length(all.par),size=1)]], approach="ss",blocks="com") plot(res) #Hopefully we get the original partition clu(res) #Hopefully we get the original partition err(res) #Error IM(res) #NULL, because FORTRAN subrutine is used.