mclust: plot.densityMclust – R documentation

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plot.densityMclust

Plots for Mixture-Based Density Estimate

Description

Plotting methods for an object of class '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

## S3 method for class 'densityMclust'
plot(x, data = NULL, what = c("BIC", "density", "diagnostic"), ...)

plotDensityMclust1(x, data = NULL, col = gray(0.3), hist.col = "lightgrey", 
                   hist.border = "white",  breaks = "Sturges", ...)

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, ...)

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, ...)

Arguments

`x`	An object of class `'mclustDensity'` obtained from a call to `densityMclust` function.
`data`	Optional data points.
`what`	The type of graph requested: `"density"` = a plot of estimated density; if `data` is also provided the density is plotted over data points (see Details section). `"BIC"` = a plot of BIC values for the estimated models versus the number of components. `"diagnostic"` = diagnostic plots (only available for the one-dimensional case, see `densityMclust.diagnostic`)
`col`	The color to be used to draw the density line in 1-dimension or contours in higher dimensions.
`hist.col`	The color to be used to fill the bars of the histogram.
`hist.border`	The color of the border around the bars of the histogram.
`breaks`	See the argument in function `hist`.
`points.pch, points.col, points.cex`	The character symbols, colors, and magnification to be used for plotting `data` points.
`nlevels`	An integer, the number of levels to be used in plotting contour densities.
`levels`	A vector of density levels at which to draw the contour lines.
`prob`	A vector of probability levels for computing HDR. Only used if `type = "hdr"` and supersede previous `nlevels` and `levels` arguments.
`gap`	Distance between subplots, in margin lines, for the matrix of pairwise scatterplots.
`...`	Additional arguments passed to `surfacePlot`.

Details

The function plot.densityMclust allows to obtain the plot of estimated density or the graph of BIC values for evaluated models.

If what = "density" the produced plot dependes on the dimensionality of the data.

For one-dimensional data a call with no data provided produces a plot of the estimated density over a sensible range of values. If 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 surfacePlot function. In particular, the density can be represented through "contour", "hdr", "image", and "persp" type of graph. For type = "hdr" Highest Density Regions (HDRs) are plotted for probability levels prob. See hdrlevels for details.

For higher dimensionality a scatterplot matrix of pairwise projected densities is drawn.

Author(s)

Luca Scrucca

Examples

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))

mclust

Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

v5.4.10

GPL (>= 2)

Authors

Chris Fraley [aut], Adrian E. Raftery [aut] (<https://orcid.org/0000-0002-6589-301X>), Luca Scrucca [aut, cre] (<https://orcid.org/0000-0003-3826-0484>), Thomas Brendan Murphy [ctb] (<https://orcid.org/0000-0002-5668-7046>), Michael Fop [ctb] (<https://orcid.org/0000-0003-3936-2757>)

Initial release

2022-05-20