groupSpread(xy, plots = TRUE, level = 0.5,
dstTarget = 25, conversion = 'm2cm')
getMOA
.getMOA
.covMcd
using the MCD algorithm.
In addition to the numerical results listed below, this function produces the following diagrams:
level
\%-confidence ellipse - the latter also based on a robust estimate for the covariance matrixgetDistToCtr
,
getMaxPairDist
,
getMinBBox
,
getMinCircle
,
getConfEll
,
getCEP
,
getMOA
,
hist
,
kernel
,
covMcd
,xy <- matrix(round(rnorm(200, 0, 5), 2), ncol=2)
res <- groupSpread(xy, level=0.5, dstTarget=25, conversion='m2cm')
names(res)
res$sdXYrob
res$meanDistToCtr
res$maxPairDist
res$CEPrand
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