R: plot Method for DiscrFact Objects

plot.DiscrFact {tclust} | R Documentation

## plot Method for DiscrFact Objects

### Description

The `plot` method for class `DiscrFact`: Next to a plot of the `tclust` object which has been used for creating the `DiscrFact` object, a silhouette plot indicates the presence of groups with a large amount of doubtfully assigned observations. A third plot similar to the standard `tclust` plot serves to highlight the identified doubtful observations.

### Usage

    ## S3 method for class 'DiscrFact'
     plot(x, enum.plots = FALSE, ...)
    plot_DiscrFact_p2 (x, xlab = "Discriminant Factor",
                       ylab = "Clusters", main, xlim,
                       print.Discr = TRUE, main.pre, ...)

    plot_DiscrFact_p3 (x, main = "Doubtful Assignments", col, pch,
                       col.nodoubt = grey (0.8), by.cluster = FALSE,
                       ...)

### Arguments

`x` | An object of class "`DiscrFact`" as from `DiscrFact ()`.
`enum.plots` | A logical value indicating whether the plots shall be enumerated in their title ("(a)", "(b)", "(c)").
`xlab, ylab, xlim` | Arguments passed to funcion `plot.tclust`.
`main` | Argument passed to funcion `plot`.

`print.Discr` | A logical value indicating whether each clusters mean discriminant factor shall be plotted
`main.pre` | An optional string which is appended to the plot's caption.
`pch, col` | Arguments passed to function `plot`.
`col.nodoubt` | Color of all observations not considered as to be assigned doubtfully.
`by.cluster` | Logical value indicating whether parameters `pch` and `col` refer to observations (`FALSE`) or clusters (`TRUE`).
`...` | Arguments to be passed to or from other methods.

### Details

`plot.DiscrFact.p2` displays a silhouette plot based on the discriminant factors of the observations. A solution with many large discriminant factors is not reliable. Such clusters can be identified with this silhouette plot. Thus `plot.DiscrFact.p3` displays the dataset, highlighting observations with discriminant factors greater than the given threshold. Function `plot.DiscrFact` combines the standard plot of a `tclust` object, and the two plots introduced here.

### Value

No return value is provided.

### Author(s)

Agustin Mayo Iscar, Luis Angel García Escudero, Heinrich Fritz

### References

García-Escudero, L.A.; Gordaliza, A.; Matrán, C. and Mayo-Iscar, A. (2010), "Exploring the number of groups in robust model-based clustering." Statistics and Computing, (Forthcoming).
Preprint available at www.eio.uva.es/infor/personas/langel.html.

### Examples

    sig <- diag (2)
    cen <- rep (1, 2)
    x <- rbind (
    	rmvnorm (360, cen * 0,   sig),
    	rmvnorm (540, cen * 5,   sig * 6 - 2),
    	rmvnorm (100, cen * 2.5, sig * 50)
    )

    clus.1 <- tclust (x, k = 2, alpha=0.1, restr.fact=12)
    clus.2 <- tclust (x, k = 3, alpha=0.1, restr.fact=1)

    dsc.1 <- DiscrFact (clus.1)
    plot(dsc.1)

    dsc.2 <- DiscrFact (clus.2)
    plot (dsc.2)

    dev.off ()
    plot_DiscrFact_p2 (dsc.1)
    plot_DiscrFact_p3 (dsc.2)

[Package tclust version 1.3-1 Index]