plotmvoutlier: Multivariate outlier plot

In StatDA: Statistical Analysis for Environmental Data

Multivariate outlier plot

Description

This function plots multivariate outliers. One possibility is to distinguish between outlier and no outlier. The alternative is to distinguish between the different percentils (e.g. <25%, 25%<x<50%,...).

Usage

plotmvoutlier(coord, data, quan = 1/2, alpha = 0.025, symb = FALSE, bw = FALSE,
plotmap = TRUE, map = "kola.background", which.map = c(1, 2, 3, 4),
map.col = c(5, 1, 3, 4), map.lwd = c(2, 1, 2, 1), pch2 = c(3, 21),
cex2 = c(0.7, 0.2), col2 = c(1, 1), lcex.fac = 1, ...)

Arguments

coord	the coordinates for the points
data	the value for the different coordinates
quan	Number of subsets used for the robust estimation of the covariance matrix. Allowed are values between 0.5 and 1., see covMcd
alpha	Maximum thresholding proportion
symb	if FALSE, only two different symbols (outlier and no outlier) will be used
bw	if TRUE, symbols are in gray-scale (only if symb=TRUE)
plotmap	if TRUE, the map is plotted
map	the name of the background map
which.map, map.col, map.lwd	parameters for the background plot, see plotbg
pch2, cex2, col2	graphical parameters for the points
lcex.fac	factor for multiplication of symbol size (only if symb=TRUE)
...	further parameters for the plot

Details

The function computes a robust estimation of the covariance and then the Mahalanobis distances are calculated. With this distances the data set is divided into outliers and non outliers. If symb=FALSE only two different symbols are used otherwise different grey scales are used to distinguish the different types of outliers.

Value

o	returns the outliers
md	the square root of the Mahalanobis distance
euclidean	the Euclidean distance of the scaled data

Author(s)

Peter Filzmoser <[e-mail]> http://cstat.tuwien.ac.at/filz/

References

C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter: Statistical Data Analysis Explained. Applied Environmental Statistics with R. John Wiley and Sons, Chichester, 2008.

See Also

plotbg, covMcd, arw

Examples

data(moss)
X=moss[,"XCOO"]
Y=moss[,"YCOO"]
el=c("Ag","As","Bi","Cd","Co","Cu","Ni")
x=log10(moss[,el])

data(kola.background)
plotmvoutlier(cbind(X,Y),x,symb=FALSE,map.col=c("grey","grey","grey","grey"),
       map.lwd=c(1,1,1,1),
       xlab="",ylab="",frame.plot=FALSE,xaxt="n",yaxt="n")

StatDA documentation built on June 7, 2023, 6:26 p.m.