# outlier: Compute outlying measures

## Description

Compute outlying measures based on a proximity matrix.

## Usage

# S3 method for default
outlier(x, cls=NULL, ...)
# S3 method for RRF
outlier(x, ...)

## Arguments

x

a proximity matrix (a square matrix with 1 on the diagonal
and values between 0 and 1 in the off-diagonal positions); or an object of
class `RRF`

, whose `type`

is not
`regression`

.

cls

the classes the rows in the proximity matrix belong to. If
not given, all data are assumed to come from the same class.

...

arguments for other methods.

## Value

A numeric vector containing the outlying measures. The outlying
measure of a case is computed as n / sum(squared proximity), normalized by
subtracting the median and divided by the MAD, within each class.

## Examples

# NOT RUN {
set.seed(1)
iris.rf <- RRF(iris[,-5], iris[,5], proximity=TRUE)
plot(outlier(iris.rf), type="h",
col=c("red", "green", "blue")[as.numeric(iris$Species)])
# }