Description Usage Arguments Details Value Author(s) References Examples
This function compares a robust covariance (correlation) estimation (MCD is used) with the classical approach. A plot with the two ellipses will be produced and the correlation coefficients are quoted.
1 2 | RobCor.plot(x, y, quan = 1/2, alpha = 0.025, colC = 1, colR = 1, ltyC = 2,
ltyR = 1, ...)
|
x, y |
two data vectors where the correlation should be computed |
quan |
fraction of tolerated outliers (at most 0.5) |
alpha |
quantile of chisquare distribution for outlier cutoff |
colC, colR |
colour for both ellipses |
ltyC, ltyR |
line type for both ellipses |
... |
other graphical parameters |
The covariance matrix is estimated in a robust (MCD) and non robust way and then both ellipses are plotted. The radi is calculated from the singular value decomposition and a breakpoint (specified quantile) for outlier cutoff.
cor.cla |
correlation of the classical estimation |
cor.rob |
correlation of the robust estimation |
Peter Filzmoser <P.Filzmoser@tuwien.ac.at> http://cstat.tuwien.ac.at/filz/
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.
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