plotuniout function

Multivariate outlier plot for each dimension

A multivariate outlier plot for each dimension is produced.

plotuniout(x, symb = FALSE, quan = 1/2, alpha = 0.025, bw = FALSE,
pch2 = c(3, 1), cex2 = c(0.7, 0.4), col2 = c(1, 1), lcex.fac = 1, ...)

Arguments

• x: dataset
• symb: if FALSE, only two different symbols (outlier and no outlier) will be used
• 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, see arw
• bw: if TRUE, symbols are in gray-scale (only if symb=TRUE)
• pch2, cex2, col2: graphical parameters for the points
• lcex.fac: factor for multiplication of symbol size (only if symb=TRUE)
• ...: further graphical parameters for the plot

Returns

• o: returns the outliers

• md: the square root of the Mahalanobis distance

• euclidean: the Euclidean distance of the scaled data

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.

Author(s)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at > http://cstat.tuwien.ac.at/filz/

See Also

arw, covMcd

Examples

data(moss)
el=c("Ag","As","Bi","Cd","Co","Cu","Ni")
dat=log10(moss[,el])

ans<-plotuniout(dat,symb=FALSE,cex2=c(0.9,0.1),pch2=c(3,21))