plotmvoutlier {StatDA} | R Documentation

## 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 <P.Filzmoser@tuwien.ac.at>

### References

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

### 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")

[Package StatDA version 1.0 Index]