R: Plots for Mixture-Based Density Estimate

plot.densityMclust {mclust} | R Documentation

## 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

### See Also

`densityMclust`, `surfacePlot`, `densityMclust.diagnostic`, `Mclust`.

### Examples

    dens <- densityMclust(faithful$waiting)
    summary(dens)
    summary(dens, parameters = TRUE)
    plot(dens, what = "BIC", legendArgs = list(x = "topright"))
    plot(dens, what = "density", data = faithful$waiting)

    dens <- densityMclust(faithful)
    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])
    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))

[Package mclust version 5.4.8 Index]