https://github.com/cran/ape
Tip revision: 88b62374d892f92ecd45527da6fe3aefd5eb8f3e authored by Emmanuel Paradis on 20 September 2002, 00:00:00 UTC
version 0.2
version 0.2
Tip revision: 88b6237
mst.Rd
\name{mst}
\alias{mst}
\alias{plot.mst}
\title{Minimum Spanning Tree}
\usage{
mst(X)
\method{plot}{mst}(x, graph = "circle", x1 = NULL, x2 = NULL, \dots)
}
\arguments{
\item{X}{either a matrix that can be interpreted as a distance matrix,
or an object of class \code{"dist"}.}
\item{x}{an object of class \code{"mst"} (e.g. returned by \code{mst()}).}
\item{graph}{a character string indicating the type of graph to plot
the minimum spanning tree; two choices are possible: \code{"circle"} where
the observations are plotted regularly spaced on a circle, and
\code{"nsca"} where the two first axes of a non-symmetric correspondence
analysis are used to plot the observations (see Details below). If
both arguments \code{x1} and \code{x2} are given, the argument
\code{graph} is ignored.}
\item{x1}{a numeric vector giving the coordinates of the observations
on the \emph{x}-axis. Both \code{x1} and \code{x2} must be specified
to be used.}
\item{x2}{a numeric vector giving the coordinates of the observations
on the \emph{y}-axis. Both \code{x1} and \code{x2} must be specified
to be used.}
\item{...}{further arguments to be passed to \code{plot()}.}
}
\description{
The function \code{mst} finds the minimum spanning tree between a set of
observations using a matrix of pairwise distances.
The \code{plot} method plots the minimum spanning tree showing the
links where the observations are identified by their numbers.
}
\details{
These functions provide two ways to plot the minimum spanning tree which
try to space as much as possible the observations in order to show as
clearly as possible the links. The option \code{graph = "circle"}
simply plots regularly the observations on a circle, whereas
\code{graph = "nsca"} uses a non-symmetric correspondence analysis
where each observation is represented at the centroid of its neighbours.
Alternatively, the user may use any system of coordinates for the
obsevations, for instance a principal components analysis (PCA) if the
distances were computed from an original matrix of continous variables.
}
\value{
an object of class \code{"mst"} which is a square numeric matrix of size
equal to the number of observations with either \code{1} if a link
between the corresponding observations was found, or \code{0}
otherwise. The names of the rows and columns of the distance matrix,
if available, are given as rownames and colnames to the returned object.
}
\author{
Yvonnick Noel \email{noel@univ-lille3.fr},
Julien Claude \email{claude@isem.univ-montp2.fr} and
Emmanuel Paradis \email{paradis@isem.univ-montp2.fr}
}
\seealso{
\code{\link{dist.dna}}, \code{\link{dist.gene}},
\code{\link[mva]{dist}}, \code{\link[base]{plot}}
}
\examples{
library(mva)
n <- 20
X <- matrix(runif(n * 10), n, 10)
d <- dist(X)
PC <- prcomp(X)
M <- mst(d)
opar <- par()
par(mfcol = c(2, 2))
plot(M)
plot(M, graph = "nsca")
plot(M, x1 = PC$x[, 1], x2 = PC$x[, 2])
par(opar)
}
\keyword{multivariate}