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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/clu.R
\encoding{UTF-8}
\name{clu}
\alias{clu}
\alias{partitions}
\alias{err}
\alias{IM}
\alias{EM}
\title{Function for extraction of some elements for objects, returend by functions for Generalized blockmodeling}
\usage{
clu(res, which = 1, ...)
partitions(res)
err(res, ...)
IM(res, which = 1, drop = TRUE, ...)
EM(res, which = 1, drop = TRUE, ...)
}
\arguments{
\item{res}{Result of function \code{\link{critFunC}} or \code{\link{optRandomParC}}.}
\item{which}{From \code{which} (if there are more than one) "best" solution should the
element be extracted. Warning! \code{which} grater than the number of "best" partitions
produces an error.}
\item{\dots}{Not used.}
\item{drop}{If \code{TRUE} (default), dimensions that have only one level are dropped
(\code{drop} function is applied to the final result).}
}
\value{
The desired element.
}
\description{
Functions for extraction of partition (\code{clu}), all best partitions (\code{partitions}),
image or blockmodel (\code{IM})) and total error or inconsistency (\code{err}) for objects,
returned by functions \code{\link{critFunC}} or \code{\link{optRandomParC}}.
}
\examples{
n <- 8 # If larger, the number of partitions increases dramatically,
# 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 partition and then optimize 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 <- optParC(M = net,
clu = all.par[[sample(1:length(all.par), size = 1)]],
approaches = "hom", homFun = "ss", blocks = "com")
plot(res) # Hopefully we get the original partition
clu(res) # Hopefully we get the original partition
err(res) # Error
IM(res) # Image matrix/array.
EM(res) # Error matrix/array.
}
\references{
Doreian, P., Batagelj, V., & Ferligoj, A. (2005). Generalized blockmodeling, (Structural analysis in the social sciences, 25). Cambridge [etc.]: Cambridge University Press.
\enc{Žiberna, A.}{Ziberna, A.} (2007). Generalized Blockmodeling of Valued Networks. Social Networks, 29(1), 105-126. doi: 10.1016/j.socnet.2006.04.002
\enc{Žiberna, A.}{Ziberna, A.} (2008). Direct and indirect approaches to blockmodeling of valued networks in terms of regular equivalence. Journal of Mathematical Sociology, 32(1), 57-84. doi: 10.1080/00222500701790207
}
\seealso{
\code{\link{critFunC}}, \code{\link{plot.mat}}, \code{\link{optRandomParC}}
}
\author{
\enc{Aleš Žiberna}{Ales Ziberna}
}
\keyword{manip}
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