https://github.com/cran/CluMix
Tip revision: 4fbb09ab94eb59bfa4196e2a4898f4e30c2845ab authored by Manuela Hummel on 21 January 2019, 08:10:22 UTC
version 2.3.1
version 2.3.1
Tip revision: 4fbb09a
distmap.Rd
\name{distmap}
\alias{distmap}
\title{Display similarity matrix}
\description{Calculates and visualizes a similarity matrix for subjects or variables in an image plot}
\usage{
distmap(data, what = c("subjects", "variables"), variables.method =
c("associationMeasures", "distcor"), varweights, linkage = "ward.D2",
reorderdend, col, ...)
}
\arguments{
\item{data}{\code{data.frame} with original data or similarity \code{matrix}}
\item{what}{Shall similarity matrix of subjects or variables be visualized?; ignored if \code{data} is a similarity matrix}
\item{variables.method}{method to calculate similarities if \code{what = "variables"}: combination of association measures (\code{"associationMeasures"}) or distance correlation (\code{"distcor"})}
\item{varweights}{optional vector of variable weights, used for calculating Gower's distances between subjects; ignored if \code{what = "associationMeasures"}}
\item{linkage}{agglomeration method used for hierarchical clustering; corresponds to parameter \code{method} of \code{\link[stats]{hclust}}}
\item{reorderdend}{optional numeric values for reordering the dendrogram (maintaining the constraints on the dendrogram), see \code{wts} option of \code{\link[stats]{reorder.dendrogram}}}
\item{col}{Color palette; defaults to blue-scale palette, where darker blue indicates higher similarity}
\item{\dots}{graphical parameters passed to \code{\link[gplots]{heatmap.2}}}
}
\details{
If \code{data} is a \code{data.frame}, the similarity matrix is calculated for subjects (if \code{what = "subjects"}) or variables (if \code{what = "variables"}).
Similarities for subjects are calculated by \code{\link{similarity.subjects}}. \\
Similarities for variables are derived by \code{\link{similarity.variables}}.
Alternatively, \code{data} can also be a previously calculated similarity matrix.
}
\value{Image plots and dendrograms}
%\references{
%}
\author{Manuela Hummel}
%\note{
%}
\seealso{\code{\link{similarity.variables}}, \code{\link{dist.variables}}, \code{\link{similarity.subjects}}, \code{\link{dist.subjects}}, \code{\link{mix.heatmap}}}
\examples{
data(mixdata)
## subjects
distmap(mixdata, what="subjects")
# example with variable weights
w <- rep(1:2, each=5)
distmap(mixdata, what="subjects", varweights=w)
## variables
distmap(mixdata, what="variables", method="association")
distmap(mixdata, what="variables", method="distcor")
}
\keyword{ hplot }