R: Symbol Plot

symbol.plot {mvoutlier} | R Documentation

## Symbol Plot

### Description

The function symbol.plot plots the (two-dimensional) data using different symbols according to the robust mahalanobis distance based on the mcd estimator with adjustment.

### Usage

    symbol.plot(x, quan=1/2, alpha=0.025, ...)

### Arguments

`x` | two dimensional matrix or data.frame containing the data.
`quan` | amount of observations which are used for mcd estimations. has to be between 0.5 and 1, default ist 0.5
`alpha` | amount of observations used for calculating the adjusted quantile (see function arw).
`...` | additional graphical parameters

### Details

The function symbol.plot plots the (two-dimensional) data using different symbols. In addition a legend and four ellipsoids are drawn, on which mahalanobis distances are constant. As the legend shows, these constant values correspond to the 25%, 50%, 75% and adjusted (see function arw) quantiles of the chi-square distribution.

### Value

`outliers` | boolean vector of outliers
`md` | robust mahalanobis distances of the data

### Author(s)

Moritz Gschwandtner <e0125439@student.tuwien.ac.at>
Peter Filzmoser <P.Filzmoser@tuwien.ac.at> http://cstat.tuwien.ac.at/filz/

### References

P. Filzmoser, R.G. Garrett, and C. Reimann. Multivariate outlier detection in exploration geochemistry. Computers & Geosciences, 31:579-587, 2005.

### See Also

`dd.plot`, `color.plot`, `arw`

### Examples

    # create data:
    x <- cbind(rnorm(100), rnorm(100))
    y <- cbind(rnorm(10, 5, 1), rnorm(10, 5, 1))
    z <- rbind(x,y)
    # execute:
    symbol.plot(z, quan=0.75)

[Package mvoutlier version 2.0.9 Index]