plineplot {klaR}R Documentation

Plotting marginal posterior class probabilities

Description

For a given variable the posteriori probabilities of the classes given by a classification method are plotted. The variable need not be used for the actual classifcation.

Usage

plineplot(formula, data, method, x, col.wrong = "red", ylim = c(0, 1), loo=FALSE, ...)

Arguments

formula formula of the form groups ~ x1 + x2 + .... That is, the response is the grouping factor and the right hand side specifies the (non-factor) discriminators.
data Data frame from which variables specified in formula are preferentially to be taken.
method character, name of classification function (e.g. “lda”).
x variable that should be plotted. See examples.
col.wrong color to use for missclassified objects.
ylim ylim for the plot.
loo Should leave-one-out estimate be used for prediction?
... further arguments passed to the underlying classification method or plot functions.

Value

The actual error rate.

Author(s)

Karsten Luebke

See Also

partimat

Examples

library(MASS)

# The name of the variable can be used for x
data(B3)
plineplot(PHASEN ~ ., data = B3, method = "lda", 
    x = "EWAJW", xlab = "EWAJW")

# The plotted variable need not be in the data
data(iris)
iris2 <- iris[ , c(1,3,5)]
plineplot(Species ~ ., data = iris2, method = "lda", 
    x = iris[ , 4], xlab = "Petal.Width")

[Package klaR version 0.3-4 Index]