mv.calout.detect {parody}R Documentation

calibrated multivariate outlier detection

Description

interface to a parametric multivariate outlier detection algorithm

Usage

mv.calout.detect(x, k = min(floor((nrow(x) - 1)/2), 100), Ci = C.unstr, 
    lamfun = lams.unstr, alpha = 0.05, method = c("parametric", 
        "rocke", "kosinski.raw", "kosinski.exch")[1], ...) 

Arguments

x data matrix
k upper bound on number of outliers; defaults to just less than half the sample size
Ci function computing Ci, the covariance determinant ratio excluding row i. At present, sole option is C.unstr (Caroni and Prescott 1992 Appl Stat).
lamfun function computing lambda, the critical values for Ci
alpha false outlier labeling rate
method string identifying algorithm to use
... reserved for future use

Details

bushfire is a dataset distributed by Kosinski to illustrate his method.

Value

a list with components

inds indices of outlying rows
vals values of outlying rows
k input parameter k
alpha input parameter alpha

Author(s)

VJ Carey

Examples

data(tcost)
mv.calout.detect(tcost)
data(bushfire)
mv.calout.detect(bushfire)

[Package parody version 1.0.0 Index]