outlierMap {cellWise}

Plot the outlier map.

Description

The outlier map is a diagnostic plot for the output of MacroPCA.

Usage

outlierMap(res,title="Robust PCA",col="black", pch=16,labelOut=TRUE,id=3,
xlim = NULL, ylim = NULL, cex = 1, cex.main=1.2, cex.lab=NULL, cex.axis=NULL)

Arguments

res

A list containing the orthogonal distances (OD), the score distances (SD) and their respective cut-offs (cutoffOD and cutoffSD). Can be the output of MacroPCA, rospca::robpca, rospca::rospca.

title

Title of the plot, default is "Robust PCA".

col

Colour of the points in the plot, this can be a single colour for all points or a vector or list specifying the colour for each point. The default is "black".

pch

Plotting characters or symbol used in the plot, see points for more details. The default is 16 which corresponds to filled circles.

labelOut

Logical indicating if outliers should be labelled on the plot, default is TRUE.

id

Number of OD outliers and number of SD outliers to label on the plot, default is 3.

xlim

Optional argument to set the limits of the x-axis.

ylim

Optional argument to set the limits of the y-axis.

cex

Optional argument determining the size of the plotted points. See plot.default for details.

cex.main

Optional argument determining the size of the main title. See plot.default for details.

cex.lab

Optional argument determining the size of the labels. See plot.default for details.

cex.axis

Optional argument determining the size of the axes. See plot.default for details.

Details

The outlier map contains the score distances on the x-axis and the orthogonal distances on the y-axis. To detect outliers, cut-offs for both distances are shown, see Hubert et al. (2005).

Author(s)

P.J. Rousseeuw

References

Hubert, M., Rousseeuw, P. J., and Vanden Branden, K. (2005). ROBPCA: A New Approach to Robust Principal Component Analysis. Technometrics, 47, 64-79.

See Also

MacroPCA

Examples

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