R: Plotting of 4 dimensional membership representation simplex

quadplot {klaR} | R Documentation

## Plotting of 4 dimensional membership representation simplex

### Description

For a 4 class discrimination problem the membership values of each class are visualized in a 3 dimensional barycentric coordinate system.

### Usage

    quadplot(e = NULL, f = NULL, g = NULL, h = NULL, angle = 75,
        scale.y = 0.6, label = 1:4, labelcol = rainbow(4),
        labelpch = 19, labelcex = 1.5, main = "", s3d.control = list(),
        simplex.control = list(), legend.control = list(), ...)

### Arguments

`e` | either a matrix with 4 columns represanting the membership values or a vector with the membership values of the first class
`f` | vector with the membership values of the second class
`g` | vector with the membership values of the third class
`h` | vector with the membership values of the forth class
`angle` | angle between x and y axis
`scale.y` | scale of y axis related to x- and z axis
`label` | label for the classes
`labelcol` | colors to use for the labels
`labelpch` | `pch` for the labels
`labelcex` | `cex` for the labels
`main` | main title of the plot
`s3d.control` | a list with further arguments passed to the underlying `scatterplot3d` function call that sets up the plot
`simplex.control` | a list with further arguments passed to the underlying function call that draws the barycentric coordinate system
`legend.control` | a list with further arguments passed to the underlying function call that adds the `legend`
`...` | further arguments passed to the underlying `plot` function that draws the data points

### Details

The membership values are calculated with `quadtrafo` and plotted with `scatterplot3d`.

### Value

A `scatterplot3d` object.

### Author(s)

Karsten Luebke, karsten.luebke@fom.de, and Uwe Ligges

### References

Garczarek, Ursula Maria (2002): Classification rules in standardized partition spaces. Dissertation, University of Dortmund. URL http://hdl.handle.net/2003/2789

### See Also

`triplot`, `scatterplot3d`

### Examples

    library("MASS")
    data(B3)
    opar <- par(mfrow = c(1, 2), pty = "s")
    posterior <- predict(lda(PHASEN ~ ., data = B3))$post
    s3d <- quadplot(posterior, col = rainbow(4)[B3$PHASEN],
            labelpch = 22:25, labelcex = 0.8,
            pch = (22:25)[apply(posterior, 1, which.max)],
            main = "LDA posterior assignments")
    quadlines(centerlines(4), sp = s3d, lty = "dashed")

    posterior <- predict(qda(PHASEN ~ ., data = B3))$post
    s3d <- quadplot(posterior, col = rainbow(4)[B3$PHASEN],
            labelpch = 22:25, labelcex = 0.8,
            pch = (22:25)[apply(posterior, 1, which.max)],
            main = "QDA posterior assignments")
    quadlines(centerlines(4), sp = s3d, lty = "dashed")
    par(opar)

[Package klaR version 0.6-12 Index]