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\name{plot.densityMclust}
\alias{plot.densityMclust}
\alias{plotDensityMclust1}
\alias{plotDensityMclust2}
\alias{plotDensityMclustd}
\title{Plots for Mixture-Based Density Estimate}
\description{
Plotting methods for an object of class \code{'mclustDensity'}. Available graphs
are plot of BIC values and density for univariate and bivariate data. For
higher data dimensionality a scatterplot matrix of pairwise densities is
drawn.
}
\usage{
\method{plot}{densityMclust}(x, data = NULL, what = c("BIC", "density", "diagnostic"), \dots)
plotDensityMclust1(x, data = NULL, col = gray(0.3), hist.col = "lightgrey",
hist.border = "white", breaks = "Sturges", \dots)
plotDensityMclust2(x, data = NULL, nlevels = 11, levels = NULL,
prob = c(0.25, 0.5, 0.75),
points.pch = 1, points.col = 1, points.cex = 0.8, \dots)
plotDensityMclustd(x, data = NULL, nlevels = 11, levels = NULL,
prob = c(0.25, 0.5, 0.75),
points.pch = 1, points.col = 1, points.cex = 0.8,
gap = 0.2, \dots)
}
\arguments{
\item{x}{An object of class \code{'mclustDensity'} obtained from a call to
\code{\link{densityMclust}} function.}
\item{data}{Optional data points.}
\item{what}{The type of graph requested:
\describe{
\item{\code{"density"} =}{a plot of estimated density; if \code{data} is
also provided the density is plotted over data points (see Details
section).}
\item{\code{"BIC"} =}{a plot of BIC values for the estimated models versus
the number of components.}
\item{\code{"diagnostic"} =}{diagnostic plots (only available for the
one-dimensional case, see \code{\link{densityMclust.diagnostic}})}
}
}
\item{col}{The color to be used to draw the density line in 1-dimension
or contours in higher dimensions.}
\item{hist.col}{The color to be used to fill the bars of the histogram.}
\item{hist.border}{The color of the border around the bars of the histogram.}
\item{breaks}{See the argument in function \code{\link[graphics]{hist}}.}
\item{points.pch, points.col, points.cex}{The character symbols, colors, and magnification to be used for plotting \code{data} points.}
\item{nlevels}{An integer, the number of levels to be used in plotting contour densities.}
\item{levels}{A vector of density levels at which to draw the contour lines.}
\item{prob}{A vector of probability levels for computing HDR. Only used if \code{type = "hdr"} and supersede previous \code{nlevels} and \code{levels} arguments.}
\item{gap}{Distance between subplots, in margin lines, for the matrix of pairwise scatterplots.}
\item{\dots}{Additional arguments passed to \code{\link{surfacePlot}}.}
}
\details{The function \code{plot.densityMclust} allows to obtain the plot of
estimated density or the graph of BIC values for evaluated models.
If \code{what = "density"} the produced plot dependes on the dimensionality
of the data.
For one-dimensional data a call with no \code{data} provided produces a
plot of the estimated density over a sensible range of values. If
\code{data} is provided the density is over-plotted on a histogram for the
observed data.
For two-dimensional data further arguments available are those accepted by
the \code{\link{surfacePlot}} function. In particular, the density can be
represented through \code{"contour"}, \code{"hdr"}, \code{"image"}, and
\code{"persp"} type of graph.
For \code{type = "hdr"} Highest Density Regions (HDRs) are plotted for
probability levels \code{prob}. See \code{\link{hdrlevels}} for details.
For higher dimensionality a scatterplot matrix of pairwise projected
densities is drawn.
}
% \value{}
\author{Luca Scrucca}
\seealso{
\code{\link{densityMclust}},
\code{\link{surfacePlot}},
\code{\link{densityMclust.diagnostic}},
\code{\link{Mclust}}.
}
\examples{
\donttest{
dens <- densityMclust(faithful$waiting, plot = FALSE)
summary(dens)
summary(dens, parameters = TRUE)
plot(dens, what = "BIC", legendArgs = list(x = "topright"))
plot(dens, what = "density", data = faithful$waiting)
dens <- densityMclust(faithful, plot = FALSE)
summary(dens)
summary(dens, parameters = TRUE)
plot(dens, what = "density", data = faithful,
drawlabels = FALSE, points.pch = 20)
plot(dens, what = "density", type = "hdr")
plot(dens, what = "density", type = "hdr", prob = seq(0.1, 0.9, by = 0.1))
plot(dens, what = "density", type = "hdr", data = faithful)
plot(dens, what = "density", type = "persp")
dens <- densityMclust(iris[,1:4], plot = FALSE)
summary(dens, parameters = TRUE)
plot(dens, what = "density", data = iris[,1:4],
col = "slategrey", drawlabels = FALSE, nlevels = 7)
plot(dens, what = "density", type = "hdr", data = iris[,1:4])
plot(dens, what = "density", type = "persp", col = grey(0.9))
}
}
\keyword{cluster}
\keyword{dplot}
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