klaR (version 0.6-7)

quadplot: 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

Value

• A scatterplot3d object.

concept

• Visualizing Classification Performance Measures
• Barycentric plots

Details

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

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)

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