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\name{nearestNeighborSepVal}
\alias{nearestNeighborSepVal}
\title{SEPARATON INFORMATION MATRIX}
\description{
Separation information matrix containing the nearest neighbor and farthest neighbor of each cluster.
}
\usage{
nearestNeighborSepVal(sepValMat)
}
\arguments{
\item{sepValMat}{
a \code{K} by \code{K} matrix, where \code{K} is the number of clusters.
\code{sepValMat[i,j]} is the separation index between cluster \code{i} and
\code{j}.
}
}
\value{
This function returns a separation information matrix containing \code{K} rows and
the following six columns, where \code{K} is the number of clusters.
\item{Column 1:}{
Labels of clusters (\eqn{1, 2, \ldots, numClust}), where \eqn{numClust} is
the number of clusters for the data set.
}
\item{Column 2:}{
Labels of the corresponding nearest neighbors.
}
\item{Column 3:}{
Separation indices of the clusters to their nearest neighboring clusters.
}
\item{Column 4:}{
Labels of the corresponding farthest neighboring clusters.
}
\item{Column 5:}{
Separation indices of the clusters to their farthest neighbors.
}
\item{Column 6:}{
Median separation indices of the clusters to their neighbors.
}
}
\references{
Qiu, W.-L. and Joe, H. (2006a)
Generation of Random Clusters with Specified Degree of Separaion.
\emph{Journal of Classification}, \bold{23}(2), 315-334.
Qiu, W.-L. and Joe, H. (2006b)
Separation Index and Partial Membership for Clustering.
\emph{Computational Statistics and Data Analysis}, \bold{50}, 585--603.
}
\author{
Weiliang Qiu \email{weiliang.qiu@gmail.com}\cr
Harry Joe \email{harry@stat.ubc.ca}
}
\examples{
n1 <- 50
mu1 <- c(0, 0)
Sigma1 <- matrix(c(2, 1, 1, 5), 2, 2)
n2 <- 100
mu2 <- c(10, 0)
Sigma2 <- matrix(c(5, -1, -1, 2), 2, 2)
n3 <- 30
mu3 <- c(10, 10)
Sigma3 <- matrix(c(3, 1.5, 1.5, 1), 2, 2)
projDir <- c(1, 0)
muMat <- rbind(mu1, mu2, mu3)
SigmaArray <- array(0, c(2, 2, 3))
SigmaArray[, , 1] <- Sigma1
SigmaArray[, , 2] <- Sigma2
SigmaArray[, , 3] <- Sigma3
tmp <- getSepProjTheory(
muMat = muMat,
SigmaArray = SigmaArray,
iniProjDirMethod="SL")
sepValMat <- tmp$sepValMat
nearestNeighborSepVal(sepValMat = sepValMat)
}
\keyword{cluster}
|
