Symbol Plot
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.
symbol.plot(x, quan=1/2, alpha=0.025, ...)
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 |
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.
outliers |
boolean vector of outliers |
md |
robust mahalanobis distances of the data |
Moritz Gschwandtner <e0125439@student.tuwien.ac.at>
Peter Filzmoser <P.Filzmoser@tuwien.ac.at>
http://cstat.tuwien.ac.at/filz/
P. Filzmoser, R.G. Garrett, and C. Reimann. Multivariate outlier detection in exploration geochemistry. Computers & Geosciences, 31:579-587, 2005.
# 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)
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