| tolEllipsePlot | R Documentation |
Plots the 0.975 tolerance ellipse of the bivariate data set x.
The ellipse is defined by those data points whose distance
is equal to the squareroot of the 0.975 chisquare quantile
with 2 degrees of freedom.
tolEllipsePlot(x, m.cov = covMcd(x), cutoff = NULL, id.n = NULL,
classic = FALSE, tol = 1e-07,
xlab = "", ylab = "",
main = "Tolerance ellipse (97.5%)",
txt.leg = c("robust", "classical"),
col.leg = c("red", "blue"),
lty.leg = c("solid","dashed"))
x |
a two dimensional matrix or data frame. |
m.cov |
an object similar to those of class |
cutoff |
numeric distance needed to flag data points outside the ellipse. |
id.n |
number of observations to be identified by a label. If
not supplied, the number of observations with distance larger than
|
classic |
whether to plot the classical distances as well,
|
tol |
tolerance to be used for computing the inverse, see
|
xlab, ylab, main |
passed to |
txt.leg, col.leg, lty.leg |
character vectors of length 2 for the
legend, only used if |
Peter Filzmoser, Valentin Todorov and Martin Maechler
covPlot which calls tolEllipsePlot() when
desired.
ellipsoidhull and
predict.ellipsoid from package cluster.
data(hbk)
hbk.x <- data.matrix(hbk[, 1:3])
mcd <- covMcd(hbk.x) # compute mcd in advance
## must be a 2-dimensional data set: take the first two columns :
tolEllipsePlot(hbk.x[,1:2])
## an "impressive" example:
data(telef)
tolEllipsePlot(telef, classic=TRUE)
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